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The process described below is what I did all this myself for purchasing a new RAV4 about two years ago. The process went very smoothly overall, and I feel very good about the purchase. I am someone who has been hit with numerous car dealer showroom games over the years (including fake buyers play-acting at a nearby sales desk pretending to compete for the same car I was interested in). In contrast, this was the best experience I’ve ever had getting a car.Since you’re talking about listed price, you must be talking about new cars, not used. Used is a whole ‘nother ball game, which I’ll come back to at the end. For new cars there is a straightforward way for you to take control of the sales transaction and ensure you are getting the lowest possible price.The short answer for explaining the game playing dynamic is that dealers are profit making institutions, and because they only see the vast majority of people once - ever, they know they have an extremely limited opportunity with you to make any profit and to maximize that profit - hence the game-playing. Imagine if every time you went into your hair cutter they tried to haggle with you. You’d stop going to that person. There’s a relationship there (usually). Normally, you go back over and over again, once you find someone you like. There is no ongoing relationship (usually) with car dealers, unless you buy a lot of cars. Besides, after your house, a car is one of the biggest investments you’ll make, and they know that. There’s a lot of money riding on it and the risks of getting it wrong are high. Your hair cutter screws up, you wait a few weeks and go to someone else; not a big deal. You get the wrong car, it’s probably going to be financially painful getting into the right one. So the dynamics of the transaction are perfectly attuned to make haggling the most likely outcome.From the dealer’s perspective, they have some wholesale price they pay to the manufacturer, and there is a published MRSP. In theory, they have to reveal their wholesale “invoice” cost to you. And while there may be ways to verify this one number, it isn’t the whole story affecting their ability to haggle or make profit. There are lots of other ways dealers get incentives and/or discounts from manufacturers that you will never be able to see. These numbers, plus the amount of profit that the dealer wants/needs to make, change frequently. The average buyer has no way to keep track of it all.In any transaction, the only thing you have control of is your own behavior (i.e. your wants, needs). With big transactions like cars, it’s common and understandable that many (most?) people start with some uncertainty about what they want. If the dealer’s salesperson smells that, they are going to try to use that to their advantage in any way they can; usually finding some way to be helpful. They know they are in competition with several other dealers, so anything they can do to ingratiate themselves to your sales process and thinking with all its uncertainty will be to their advantage in winning the deal. Of course, all that helpfulness isn’t free - you’ll be paying for it in one way or another.Back before the internet, the only way to learn about cars was to go to dealerships and ask questions, and get answers. Sorting it all out, especially if you go to more than one dealer is difficult. Today, you can get pretty consistent answers without talking to anyone - you just have to be willing to spend some time on the internet. You can even look up the inventory of stock at each dealer.Here’s the key to taking a non-illusory control of the car-buying transaction: hold a seller’s auction for a very specific make/model/trim of a new car. Ideally, you live in a medium-sized (or larger) metro area, or are willing to dedicate at least a day to travel to one. The premise is that new cars, to the dealers, are commodities. To the dealer, they are just widgets. If they have 15 Toyota RAV4s with the Limited trim on the lot, they each represent the same profit making potential to the dealer. You can use that fact to your advantage if you remain disciplined in your buying process. You don’t need to know in advance how much they paid for it. You don’t even really need to care; even though they’ll offer to “show you the invoice” with all kinds of gravitas and ceremony about what they’re revealing to you.You may also see questionable value add-ons (a so-called “loaded” car) which are done to the car at the dealer and represent high-profit opportunities for the seller (e.g. undercoating or paint coatings, etc. - anything that wasn’t done by the manufacturer). These will actually work against the dealer’s interest in a seller’s auction approach. Despite their earnest sales pitches, these add-ons are of little real value to the buyer. If they were of such high value, every car would get them, and the manufactures would just do it at the factory. Dealers don’t do them for every car, because they can’t convince everyone of the dubious value, so they won’t risk “ruining” all their stock with stuff that they can’t sell or jack up the price enough.The other way that dealerships make money off new car sales is through financing. But you have to resist getting into that question before it’s time. You should get non-dealer financing lined up in advance, and you’ll settle the price of the car first before even beginning the discussion of financing. Don’t allow financing to become part of the decision for which car at which price, or you’ll be giving up a lot of control.Here are the steps:You have to know exactly what you want and that decision has to be final. This means you ultimately narrow down the new car you want to a single year, model, and trim with a fairly narrow range of colors. Feel free to run around to dealers doing test drives and getting information. Be friendly with sales staff, but make no commitments and be very tight-lipped about your approach, or even what you prefer. Give vague answers. Q: “Do you like that model?” (referring to the one model you’re zeroing in on) A: “Oh, it’s nice, but I’m just looking right now.” Once you make your decision, don’t ever let sales staff talk you out of it. They love to see you waver - it gives them an opportunity to try to be helpful. Spend as much time as you need in this step so that your final decision is truly final.If you test drive a car that is definitely, or is likely to be, your final Year/Make/Model/Trim target, make sure to get a picture of the full window sticker, and make sure it has the VIN on it (it should). If the VIN is not there, get it from the driver’s side dash (the metal plate visible through the windshield). Don’t make a big deal of this, just do it without giving off unnecessary clues as to why you’re doing it. Salespeople will ask you about your buying process. Be vague, and don’t reveal anything about an auction or bidding. Just saying you’re “considering options” is enough.Get your financing (if needed) lined up in advance. Do it through your bank or your credit union. Have them give you a letter certifying that you qualify for a loan, and ideally have it be for an amount that’s way above your expected price range. That way if you wind up needing to show it to the dealer down the road, they don’t get any useful clues as to how much you can afford. Later, if you want to consider the dealer’s financing, you can, but you will now have a reference point on which to compare. They can either beat it or they can’t, but that’s a separate decision apart from which car and which selling price.Figure out what’s in stock in your area. Start by doing some homework on the internet. Sites like Autotrader.com have listings of (almost) every new car in the region, with full descriptions of the car including the VIN. Create a table (spreadsheet) of every one of the units which are currently in stock. Plan to do this actively over several days, but don’t let it drag on too long. The available stock in a metro region will constantly be shifting. A new car arrives at the dealer on a car-hauler. It sits on the back lot a few days while it goes through “pre-dealership inspection”. If they’re going to give it add-ons, this is when they do it. Eventually it gets moved towards the front, and the sales staff actively start trying to sell it to people who show up at the lot. But for your purposes, the moment it drops off that car-hauler, it’s fair game for a seller’s auction. You might even be told about a unit that fits your criteria that is going to be delivered soon. Get the delivery date and the VIN and all the other info about it. All that matters to you is that it fits in with your Year/Make/Model/Trim and color(s) specification. When you’ve identified a handful of dealers, it isn’t bad to go visit and ask to see everything they have in your specification. Tell them you want to everything in the spec, including stuff that’s not through inspection yet. This way you’ll see stuff which is fresh off the truck and isn’t yet listed anywhere. Refuse their attempts to show you anything else. Be polite but be single-minded. You’re only there to identify what they have on the lot. Take pics of the car, the sticker, and make sure you get the VIN. You shouldn’t need to test drive during this visit; you’ve already made that decision. And it’s a new car, it should drive no differently than the others like it that you’ve already tested.Sit down with your spreadsheet and see how many options you have out there available for purchase. Ideally there are 10 or more of the same specification through a decent sized metro area. If it’s a popular car, like a Toyota RAV4 in a major metro area, you could have 30 or more on there. Your spreadsheet should show the VIN and the dealer. It’s good to add the name of any sales person you spoke with and any notes about color, and minor options like roof racks, etc. The sales person you talked to may not be the one who ultimately closes the deal with you, so phone the dealer’s main sales line and ask if they have an “internet sales” department. Usually that’s just one person on their staff, so get that person’s name, phone and email and add it to your spreadsheet. No worries if that person doesn’t exist. Then just make sure you have the name/phone/email of the sales person you talk to on each lot. If you visit a lot more than once, it’s good to try to speak the same salesperson. Someone’s going to make a commission off your sale, so you might as well be friendly with someone, even if you’re not going to play the game the way they would prefer. Also keep track on the spreadsheet of each unit’s MSRP as well as the dealer’s suggested price (which may not be the same number). Even though you are going to set up an auction, every single unit in your specification may not be perfectly equal; there may be minor differences. For example, one might have a roof rack, or another has higher-grade floor mats. Try to ignore the dealer-added options and pretend they don’t exist. Work through your list and decide (and mark) which of the units you are willing to receive a bid.Compose a generic “invitation to bid” letter. You will send this as an email to each dealer which has at least one of the units in your spec that you want a bid for. Ideally, you’ll send it out at 8 or 9am in the morning, and you start the letter by telling them that at some specific hour today (say 1:00pm) you will be making a final decision to purchase a car. Give them a few hours to respond, but not too much time. Setting the “final bell” at 1:00pm allows you time to work out any last minute glitches, and then you still have time before the end of the day to go to the dealer and complete the paperwork. In the letter, tell them the exact Year/Make/Model/Trim, and acceptable color(s). State clearly that you will only entertain bids for units that this spec and no others. Tell them that there are other dealers in the area that are also being invited to participate in this bid, but don’t say who. Also don’t send one single email out to several dealers at once. Send only separate emails to each dealer with the identical language. Give them a list of specific data-points you want to see in their response. Besides the obvious (your specification), it should include the VIN, their stock number, current status (is it on the lot or scheduled for delivery), and any options. If the unit meets your spec, but doesn’t have something you’d like (e.g. a roof rack), then have them specify separately the cost to add it. Have them state their complete offering price, including (a break out of) price, incentives, taxes and fees, and a “final sales contract price”. Tell them that you will not consider any offers which have any conditions, such as dealer financing. Financing is something you will consider only after the car the price are agreed to. Tell them that you will not add any value or consideration for dealer extras which may have been added to the vehicle. They can tell you about these options if they want to, but the only thing under consideration is price (presuming the unit is within your specs). Tell them that you will notify the winner of the bid at the specified time, and then you will immediately come down to the lot to sign the paperwork and take possession of the vehicle. Tell them that their offers have to be by reply (in writing) to the email.As soon as you’ve sent out the emails, then call each dealership and ask to speak with your contact. Make sure they have seen the email, and ask if they intend to bid. Then sit back and wait for phone to ring. Don’t be surprised if you hear from the sales guy who took you out on a test drive, but his dealership also has an internet sales department which is who you sent the letter to. He may give you a sob story of some sort. Maybe it’ll be that he’ll get aced out of a commission because the internet sales dept now has the sale. Maybe it’ll be about how he thought “we had something going together” with all the helpfulness he showed you. But if you made no commitments earlier, then you have nothing to be worried about. This is just a normal reaction to the transaction getting out of his control. None of it matters. Just stick to your process, and tell him politely that this is the way you’ve decided to buy a car. Don’t agree to change your deadline. Then ask if he intends to bid. Don’t answer any other questions, like, “Which other dealers are in play?” Repeat only what was in your letter and leave it at that. Most likely the test-drive sales guy isn’t completely out the picture, but now he has to huddle with another sales guy and their manager, and they figure out a bid price. Maybe he has to share his commission. Who knows - but it is not your concern. You’re buying from the dealer as a whole, not any one person.It may be that not every dealer will bid. But when the bids start coming in, add them to your spreadsheet. Then analyze what you have received. If you’re truly bidding exact copies of the model with no variance, then picking the lowest number is easy and obvious. But if you’ve got slight variations, you have to decide maybe based on something else. What if one has a roof rack that you don’t care about, but another doesn’t? How do you compare and rank order them? If no bid jumps out at you as the obvious one, you might try comparing on the basis of which dealer has taken the lowest profit. One way is to do a bit of math to see which bid represents the greatest percentage discount off of the manufacturer’s MSRP. That is the only number that is published and can be used as a kind of reference point. What you don’t know is the dealer’s *actual* wholesale cost, taking into account their invoice amount, plus any incentives or discounts that only they know about. On top of that, you don’t know how much profit the dealer wants or has to make. That number may vary from week to week or day to day or model to model. The only thing you can be sure of is at this point in time (e.g. 1:00pm on the day you select), every dealer on your list has a preferred profit point and a certain set of units in stock that fit your criteria. So the sellers auction process is the best way to find out which dealer will tolerate the lowest amount of profit, which is to your benefit. In any event, make a decision, and make it as close to your deadline as possible. And make sure they have at least sent you an email confirming the price offered, specifications, VIN of the vehicle offered, and any conditions.Now it’s time to go close the deal. Don’t immediately call the runner up bids; but do call the “winning” dealer and confirm what you saw in the email with your contact. Don’t tell them that they are the winner, and don’t tell them that you “accept” - this could arguably complete a legal contract (at least verbally), which you’re not quite ready to do yet. Just say you want come “see the paperwork”, and make an appointment to head down there immediately. Avoid taking calls from your runner up bids (they will call you once the deadline passes) until you’ve seen and signed the sales contract that comports with the deal you think you’re getting. If the paperwork they present you is any different, and they will not adjust it on the spot, then walk. As you head out the door, if you want to play the same kind of drama game on them that they typically play with customers like you, make your runner-up call conspicuous (but not so they can hear the details). Head right over to your runner up and don’t look back. By changing what they offered, the first dealer should forfeit the right to even close it. You could probably haul them into court to try to enforce what they sent in their email offer, but I’m not a lawyer, and I suspect that it would not be worth the hassle. Just head out to your runner up.Financing and other issues: when they close the deal, the dealer’s salesperson will typically pass you off to the “finance department”. Despite the fancy title, this is really just a more experienced salesperson who, while completing the paperwork, will still try to upsell you on other things like financing, extended warranty, extras, and goodies. Now that you’ve settled on the car and the price, these discussions are easier to have because there are fewer pieces on the chess board for them to move around. They can’t play the typical game of giving you a discount here, but jacking things up somewhere else - at least not as easily, and only if you let them. If you already have your bank’s financing letter, then they will either beat that offer or not. Make sure you know in advance how to compare financing offers - it’s not difficult if you’ve studied up on it. If you stick with your own financing, hand over the letter after you see the contract and price to your liking. They’ll then complete the sales contact presuming your financing not theirs. They’ll also try to sell you a whole list of upgrades and extended warranties. It’s good if you do a little homework on these in advance. The extended warranty might or might not make sense to you; but it’s better if you consider it on its own merits and not confuse it with the basic car and price decision. Don’t let them offer to give you a discount on an extra goodie if you just agree to change the basic sales price of the car. If you allow this, then you’ve completely undermined everything you accomplished in your sellers auction process. All things beyond the basic car and price should be thought of as separate products, and whether they have value to you is up to you. Generally these goodies are high-profit items to the dealer, so if they’ve allowed themselves to bid an excessively cheap price on the car, they may try to make some of it back up. You will have to wrap these questions up in the same final sales meeting, so do your homework. Plan on this final sales meeting to take at least an hour, maybe longer if the car isn’t quite ready for you to drive it off the lot. But if they’ve agreed to immediate delivery, they will have the people needed to do any final prep.When it all looks good on paper, drive your new car off the lot and congratulate yourself for getting the lowest price that was possible in town on that day for that car.A note on Used vs. New: the commodity nature (to the dealer) of new cars makes this process pretty simple to work with because you don’t have to know in advance exactly how much the car is worth or what the dealer actually paid for it, or how much profit they have to make (on that day). The auction process, if you stick with it, will render that number for you in the end. You might also consider aiming your bid process towards the end of the month, quarter, or year because sales managers have numbers quotas to meet, so their willingness to stretch is generally greater just before those moments in time. For used cars, you can still hold an auction, but there is less certainty about getting the “best” deal unless you really know used cars and their value, and the kind of mechanical condition that they are in.Hope this helps.

I attach below an edited transcription of a Q&A session titled “Academic Careers vs. Industry Careers” given by Greg Duncan and Guy Lebanon to summer interns at Amazon in the summer of 2014. Some of the content is specifically aimed at the fields of machine learning, statistics, and economics. The content does not reflect the official perspective of Amazon in any way.It was also published at Medium (Academic Careers vs. Industry Careers)Q: What are your backgrounds?Greg: I am the Chief Economist and Statistician in GIP. I do a variety of things and depending on what day you are talking to me I’m one of an economist, a statistician, a machine learner or a data scientist. I have a PhD in economics, an MS in statistics, and a BA in economics and English. I work on a variety of statistical and forecasting issues in our Global Inventory Planning process, and I do data science consulting generally within Amazon. I am responsible for the algorithm that powers the buy box on Amazon’s web site.I have 40 years of experience in data science, economics, and statistics. I was a full professor in both economics and statistics and had faculty appointments at Northwestern (6 years), UC Berkeley (12 years), WSU (9 years), Cal Tech (2 years), and USC (3 years). Currently, I have a part time appointment at UW’s economics department in addition to my full time position at Amazon. I’ve had joint positions between industry and academia for most of my career. I’ve supervised more than 20 PhD dissertations and 18 of them are full professors, some of them in good places: CMU, Maryland, UCSD, and the University of Wisconsin. I have an early 1980 paper that lays out map reduce and mini-batch SGD (though using other names).I quit publishing in 1989 since I was at Verizon and GTE labs and they didn’t allow publishing. I was the chief scientist at GTE lab and I led the team that designed the spectrum auction algorithm for the Verizon wireless network. I also designed and fielded hundreds of consumer preference surveys. I then transitioned to consulting and worked at National Economics Research Associates (NERA; a Marsh McLennan firm) as senior VP and management committee member. Later I was Managing Director at the consulting firms Huron and Deloitte, and a Principal at the Brattle consulting group. I then retired, but about two years ago I came out of retirement to join Amazon.Guy: I grew up and went to college in Israel. I came to the US in 2000 for a PhD at Carnegie Mellon University. I graduated in 2005 with a thesis in the area of machine learning. It was clear to me since my sophomore year in college (1997) that I wanted to be a professor. I’ve worked towards that goal in a very focused way from 1997 to my PhD graduation in 2005. I was lucky to get a faculty job right after graduation and I joined Purdue as an assistant professor in 2005. Due to a two-body situation and geographical constraints I decided to move in 2008 and I ended up at at Georgia Tech. I got tenure and promotion to associate professor at 2012 and then went on a one year sabbatical at Google. At the end of my sabbatical my wife and I decided to stay on the west coast and I decided to stay in industry, but move to Amazon rather than stay at Google.Q: What are your main messages about careers in industry vs. careers in academia?Greg: Here are my main points:(a) There is a lot more freedom in academia than in industry, but the problems are not as interesting.(b) The stuff you do in industry ends up actually being used.(c) Industry jobs pay well, while academic jobs do not.Guy: First, I would like to point out that there is no objective right choice here. There are pros and cons and the right answer depends on the person, and possibly even the specific time in a person’s life. For example, for me the right choice in 2005 was to join academia, but in 2013 it was to move to industry.The main pros of academic jobs are:(a) Freedom. Despite what some recent blogs say about professors not being completely free due to their need to publish and get grants, there is much more freedom in academia than in industry. This is true for young faculty members, but it is especially true for senior faculty members. They do not report to a manager in the same sense that they would in industry. As long as they remain somewhat active in publishing and grants, they can work on whatever they want.(b) Theory. Academic jobs are much more suited than industry jobs for people who want to work on theory. This is true for pure mathematicians and for CS theorists, but it is also true for people who mix theory and algorithms.(c) Teaching. Not everyone likes to teach, but if you do then this is a huge pro. I like teaching and I felt a lot of satisfaction from teaching students of all levels.(d) Stability (see below).The main pros of industry jobs are:(a) Big Impact. A few people can accomplish something truly big and important on their own. Albert Einstein comes to mind. The other 99% need a lot of help, especially in computer science. The help includes a team, proprietary data, and massive computing resources that are all generally unavailable in academia. I want to clarify that I’m talking about really big accomplishments that revolutionize our world, for example, the Internet, cloud computing, smart-phones, and e-commerce. These revolutions all required a lot of people working together and a lot of financial support. In academia you can develop some theory that will influence these revolutions to some degree but it is very rare to actually be the main driver of these revolutions.(b) Teamwork. Academic work is pretty solitary. Professors meet periodically with their students and colleagues, but it doesn’t come close to the teamwork that you find in industry. Some people prefer to work alone, and that is fine (notice my point above though that real impact requires teamwork). But for people that enjoy being a part of a team or leading a team this aspect of industry can be a big pro.(c) Two Body Careers and Geography. In the high-tech industry it is fairly easy to find a good job in many regions. For example, you can find many good opportunities in the US at San Francisco, the bay area, Seattle, New York City, Los Angeles, Boston, and Chicago. Some of these locations have more opportunities than others, but a good candidate can find good options in any of the above locations, and many other locations as well. In academia, a typical applicant sends 10–50 applications all over the country, and if they are lucky they get one or two offers — likely in places that are not their top choices. This is a problem for the professor, but it is an even bigger problem for the professor’s spouse, who is likely to have a separate geographic preferences.(d) Compensation. Compensation is much better in industry than academia. The compensation gap is minimal right after PhD graduation, but it widens significantly with time. It depends on many factors, but is quite possible for the pay gap to grow to more than 100% after 10 years (possibly significantly more than 100%). Many young PhD graduates don’t consider this a priority right away, but this becomes a bigger priority later on when the graduates plan on having kids, buying a house, etc.(e) Opportunities (see next paragraph).Workplace and role stability is much higher at academia and it can be both a pro and a con. It is a pro since it is nice to not worry about what happens next and being able to make long term plans. It is a con since stability is negatively correlated with new opportunities. In industry people frequently leave and roles change and this can often lead to exciting new opportunities. For example, my immediate manager at Amazon left a few months after I started. This caused some unexpected issues for me, but things turned out very well at the end — I got an opportunity to interact directly with Amazon’s leadership team. Industry is full of opportunities, but one has to be ready for some amount of instability.There are two stories that I want to mention next that are relevant for this discussion.Story 1: As a professor and graduate student, I noticed that professors often “brainwash” graduate students that academic jobs are the best path forward for the best students, and that industry jobs should only be entertained if a faculty search is unsuccessful (or is unlikely to be successful). Professors convey this message to their students since they believe it to be true (after all they ended up being professors because that is what they believe). But there is an added incentive for professors to do that: placing your graduate students as faculty in top departments increases your reputation and your department’s reputation and ranking. Indeed, the placement of graduate students as professors in good schools is a key component in how professors and departments are evaluated (both formally and informally). I personally witnessed department chairs and deans urging professors to push their top students to faculty jobs rather than industry.While at school, graduate students receive this message from their thesis advisors and other professors they look up to. I want to offer here a different perspective and hopefully help people understand the relative pros and cons so they can make the best decision for themselves.Story 2: A couple of years ago after getting tenure at Georgia Tech, I had a minor midlife crisis. I could choose to proceed in many different paths as a tenured professor, but I didn’t know what to choose. I could focus on teaching or writing a book; I could keep writing research papers in my current area, or switch to a different research area. I started writing a book. I studied for some time new research fields (computational finance and renewable energy) — thinking that I may want to change my research direction. I eventually understood that the main question I need to answer is: “what do I want to do for the rest of my life?” This question is highly related to the question “looking back from retirement, what accomplishments will I consider to have been successful?”The key insight for me was: publishing papers, having others cite my work, and getting awards is simply not good enough when the alternative is improving the world. In the future, when my kids ask me what I did during my long work days I want to point to more than a stack of papers, decent pay, and a length CV. I want to say that I played a big role in helping society and changing the world for the better. The chance of doing that in industry is much bigger than in academia. We are living in a unique age of increasingly fast revolutions: computers, Internet, e-commerce, smartphones, social networks, e-books. These recent revolutions were all driven by companies like Amazon, Apple, Google, Facebook, and Microsoft. We’ll see many more revolutions in our lifetime including wearable devices, self-driving cars, online education, revolutions in medicine, and more. I do not mean to say that I can change the world by myself in a couple of years, but with the help of colleagues and over the period of several years it is possible.Greg: I found most of my research topics in the nexus of computer science, economics, statistics, applied math, and psychology. At Amazon these areas are like tectonic plates hitting one another. Economists can do some things, statisticians can do other things, and data scientists can do other things. If you are in academia, it is not easy to work in that nexus. Many colleagues in the statistics department would say that is nice work but it is not really statistics stuff. The same thing would happen in computer science and economics departments. I find working in that nexus to be very exciting. It isn’t clear what to do, but you realize that there is a problem and no one knows how to work on it. Another related issue is that in industry you need to solve a specific business problem, not a related problem as is often done in academia. It’s a kind of freedom, but it is also a restriction. It’s like writing a sonnet — you can do anything you want as long as you maintain its form.I really like working at Amazon. Another place I had a lot of fun was Verizon where I had a lot of impact. When I see people buying stuff from Amazon I can point and say I helped make this work well. Similarity, when I see people using Verizon phones I can say I helped develop that technology.In my area of economics and statistics you probably want to go to academia first, have your midlife crisis, and then move to industry. My mid life crisis, by the way, was having three kids preparing to go to college and realizing that even a senior tenured professor at a good university can’t send them to college and can’t buy a house. Perhaps an industry postdoc position would work well, in that people don’t go straight to a faculty job but would have some industry experience first. Unfortunately, that does not happen frequently in economics or statistics.Q: What limitation does an industry job places on future jobs. What if you choose industry first and then have a mid life crisis and want to move to academia?Greg: In economics or statistics that would be a killer. However, I think in a growing field like data science perhaps you can switch to academia after industry. I think it is important to keep a connection with universities even when you are in industry. I have done that for much of my career. In fact, I recently taught a course on data science and I put the syllabus on the web. I got many requests from academics asking me to come and teach for their departments since they are trying to start an ML group.Guy: This would not be a big deal if you are going to industry for a short amount of time (1–3 years) and then apply for faculty jobs. If you are in industry longer and want to keep the option of moving to academia you need to find a place that allows and even encourages publishing. You don’t have to publish like crazy but you need to keep publishing. I also think that sometimes the most interesting papers come from industry since they work at a scale that academics don’t have access to. Such papers are worth more than typical academic papers experimenting on standard public datasets and will be very valuable if you later apply for faculty jobs.In machine learning, cutting edge is increasingly done in industry since academics don’t have access to the really interesting data, evaluation methods, and computational resources. It is already impossible for academics to reproduce large-scale ML experiments described in industry papers and build upon them and this will become more common in the future. Once this happens more frequently, algorithmic and applied ML innovation will occur primarily in industry.Greg: I want to amplify that. I get a lot of requests from former colleagues of mine that ask me to give them interesting Amazon data so they can work on it. The answer is usually no and not just at Amazon — Google and other companies would usually say the same thing. In industry you have access to datasets that academics can only dream of. You will be picking up stuff that is quite relevant and the market values that human capital significantly. Sometime universities hire industry veterans — for example USC does that. These veterans may not have PhD degrees even, but they have experience that is extremely valuable and generally unavailable in academia.Guy: I want to mention a related issue. In academia the mindset is usually you join a department and you stay there until retirement. Perhaps you move from one university to another once in the middle of your career. In high-tech industry the mentality is very different these days. Many people join a company and then move after a few years, and then move again. Transitioning form one company to another is especially easy if you live in a high-tech hub like the bay area, Seattle, or New York City, but it happens in other places as well. As a result, young graduates should not feel that choosing between different industry options is a huge decision that will design their entire career without a possibility to backtrack from it.Greg: That is a good point. In academia I can’t tell you the number of times someone made me an offer and I said no I’m not interested, and then something changed and I called back after two years expressing interest and they said sorry — we can’t reissue that offer at this point. That absolutely doesn’t happen in industry. It’s almost like fishing — we didn’t get you this year but we’ll try again next year. Maybe you will be upset for some reason and we’ll be able to get later. The key thing is we are in a growing and expanding industry and as a consequence experienced people are in high demand.Q: If you knew you were going to industry anyway would you still get a PhD and would you do anything different?Guy: That is a very good question and if you look at the web there are a lot of blog posts discussing whether a PhD is worth it if you end up in industry. It’s a parallel discussion to the discussion of academic vs. industry careers in that there are pros and cons and no right or wrong answer. It depends on the person, and the specific mindset they have at that point in their life.In my case, I definitely do not regret doing the PhD. Doing a PhD means losing considerable money (often in terms of opportunity cost), but the way I see it one should optimize for their long-term career rather than for a 5–10 years horizon. If you do a PhD and move to industry, in some sense you lose 5 years, but there will be enough time in your future 30–40 years to make up for that financially and otherwise. The PhD experience will likely be the only time in your life where you can look at a problem and study it and become a real expert at it without distractions. In industry you have distractions like needing to launch a product or fixing an urgent problem, and you may not be able to learn fundamental skills that take years to develop. For example, a deep understanding of machine learning requires deep knowledge of statistics, probability, real analysis, linear algebra, etc. If you are working on an ML product in industry you just don’t have the time and peace of mind to dive deep and properly learn all these areas. I also think it is an enjoyable experience and it shapes your personality in some way. There is plenty of time afterwards to worry about product launches and changing the world.Greg: I have a different perspective. In economics you really need a PhD and in statistics it is getting to the point where you really need a PhD to do scientific work. The reason is that we have a mature discipline now. In the 1950s a very smart creative MS or even BS could become a professor. These days I can pretty much tell who has a PhD and who doesn’t based on the way they think. In my area, when you get to the MS level you feel like know everything, and everyone at that level knows everything. If you do a PhD, your thesis advisor says tell me something we have never heard of. You have to demonstrate your creativity and you have to learn how to be creative and solve problems that are ambiguous and aren’t well defined. The best theses are in areas where people may not even know that there are problems and as a consequence people are doing things incorrectly. Such significant creativity does not usually come from people that didn’t get a PhD since they didn’t develop that mindset. And so not having a PhD stands out much more than 60 years ago.Guy: I agree with Greg, but I don’t think it is quite as pronounced in computer science. You do normally need a PhD to be a scientist, but there are a lot of exciting innovations that can be accomplished without a PhD experience. I also want to say that being a scientist is not the only way to do exciting things and make a significant impact. You can be an engineer, a product manager, a people manager, UX designer and you can do amazing things that change the world.Greg: I agree. I was referring to a research scientist working in areas of statistics or economics. Also, if you want to go the business route a PhD is not very relevant — you should get an MBA instead.Q: What about publication policy at Amazon and at other companies?Greg: If you are doing something that is very relevant to Amazon the last thing you want is to publish it and have a competitor get it. At Verizon and GTE lab we had a no or minimal publication policy. We thought Bell labs messed up and gave their stuff away. On the other hand, people who are starting their careers do need to publish, and I am sympathetic to balancing the need for having people know about you and your work. Early in your career it is important to publish, which is why I think it makes sense to have an academic job first.Guy: I think companies should publish to some extent, assuming their business interests are maintained. Many companies including Amazon have a publication policy where people submit a request to publish a paper and someone goes over the request and decides whether to let you publish, ask you to change the paper, or just prohibit it altogether at this point in time.Q: What about choosing between a researcher career and a software engineer career?Guy: I want again to clarify a misconception that researchers in industry are better or more senior than engineers. That is simply not the case. For example my manager is a business person and doesn’t have a PhD, but I have a lot of respect for him, his experience and what he accomplished. I have no problem taking directions from a manager, regardless of whether he is a scientist, an engineer, or a business person. Similarly, I have a lot of respect to my colleagues in different job ladders. Unless you are at a place that focuses on pure research (like MSR, though that may be changing there as well), the goal of both scientists and engineers are the same: develop a great product and help the company and its customers. People in different job ladders would have different strengths but everyone works as a team to get things done. A software engineer would have really strong skill set in one area and a scientist would have a really strong skill set in another area.Q: How did you feel your impact change when you moved from academia to Google and when you moved from Google to Amazon?Guy: When I was in academia I felt that I had an impact — people cited my work and told me that they liked my paper and that it inspired them. I got invited to give talks and received a few awards. I felt good about myself and my impact. But when I moved to industry and saw how industry is rapidly changing the world, it put the academic impact in perspective. What I previously thought of as big impact all of a sudden became minor and elusive. It was hard to point at concrete long-lasting ripple effects that my work had on the real world (except the influence I had on my students).When I was at Google, I was officially on sabbatical and I kept the option of going back to academia open. This resulted in some lack of focus and so my impact at Google was mostly scientific. At Amazon I officially resigned from Georgia Tech and jumped with both feet into an industry career. That changed in mindset and resulted in having a more profound product impact.Greg: I, too, went on sabbatical to GTE Labs and I intended to come back, but afterwards decided to stay in industry. I had a good publication record and citations, but it wasn’t the kind of impact that I had at Verizon or that I have here at Amazon. The impact you can have in industry is real and immediate. It’s like baking bread in that you work hard and the loaf comes out and you eat it — instant gratification. In academia you submit your article, and then you wait a while and the reviews come back with revise-and-resubmit decision. Then you wait a bit and you go back and do some work, and then resubmit. Perhaps at the end it gets into the journal but by the time people read and ask me about it, I’m working on something else and sometimes I even hardly remember that paper. I remember that somebody asked me about a paper recently and I had to look it up — I forgot I even wrote it. The point is that impact in industry is real and palpable and people note it. Also, about politics: many businesses are political, but what I’ve seen is that they are less political than any economics or statistics department I’ve been in. Perhaps Guy can comment on politics in CS.Guy: At Purdue’s ECE department there was quite a bit of politics that actually shocked me as a new assistant professor. The other departments I have been at were not very political.Q: How do you compare work life balance between industry and academia?Greg: I think work life balance is a lot better in industry. In academia for the first 10 years people are very focused on getting tenure and then getting to full professor. If you are not working on weekends — you are not going to get promoted. It’s as simple as that. At Amazon and at GTE Lab and Verizon you can organize your time so that you have more time for your family. On the other hand, we are all professionals and most of us would do the work for free. I’m the luckiest person in the world since they pay me for doing something that I love doing.Guy: I had a different experience in that I don’t think work life balance at academia has to be much worse. There are about 3 years where I was working particularly hard and I’ve seen my colleagues work particularly hard (years 2–4 of tenure track). In general, I was at work from 8 in the morning until 5 in the afternoon with occasional extra work later at night if needed. I do the same thing right now in industry. I do think it depends on each person and in both industry and academia there are workaholics or people who are influenced by workaholics to work very long hours.One nice thing about academia is that work is more flexible and you can work from home (or other places) more. Also, it is really nice to have the academic flexibility during the summer semester.

Well, beside Erik Fair, the most active people tended to work as admins, software developers, etc. and they many times have a wide variety of interests. Part of the reasons for this early on was merely for periods of testing in new news groups. I’d hang with a new group for the first couple dozen posts to make certain it was propagating well.Most general users tended to stay in interest groups more. Nelson Brown was in sci.aeronautics with our mutual coworker Mary Shafer who was the moderator. David Ecale worked for Cray and was part of the supercomputing groups and comp.unix.cray. Victor Eijkhout not only was on usenet but also the numerical math mailing list started by Jack Dongarra who also certainly lurked in various sci.math groups. David Koblas is a skier, nearly a roommate, and married one of my coworkers, and he was on the net.ski, and rec.skiing.alpine hierarchies. And so on, and we all back-channel communicate, have email and phone contacts, etc. Craig Good worked for Pixar and was a member of my SIGGRAPH chapter, I think. Carey Sublette posted on sci.military (which was also moderated). And there are many more depending on topics and interest.Oh, this is about the people yourselves.I was an ARPAnet hack frosh in 1973 as an out transfer nuclear engineering major (into math). I knew about ARPAnet mailing lists in 1982 (@ames-67) with SPACE-DIGEST which over the course of about 3 years I developed the concept of FAQs: not proud of this, more annoyed (like frequently here on Quora (product)). In turn with gatewayed mailing lists and news groups, these would justify the various *.answers news groups (like comp.answers, sci.answers, other Big-7 hierarchies, local hierarchies like ba.answers, ca.answers) for cross posting FAQ posts per other news groups in different hierarchies.I started in 1982 on Usenet, when I moved to the Bay Area from UCSB and Pasadena. Peter Gross (hao!pag) had set up a first connection to ames-lm! I asked James Alien Woods, and Doug Kerr for a guest account “Keep it under 1,000 blocks Doug said.” These friends were contractors. I put out Tom Ferrin’s vtroff on a little heavily used PDP-11/70. It was a smash. That software would justify their organization a VAX-11/750.I was picked to monitor and to hire hard to employ talented fresh out high ranked college graduates. NASA needed people. NASA was struck in a cold war mentality as well as anti-computer (minimal use of computers). I ran the first Usenix and /usr/group supercomputer BOFs (dmr came and had interest for Bell Labs). This is very short. I knew many of these guys from JPL and earlier Usenix meetings.My best social media story which is the story of open source: at the time Network Systems (NSC) Hyperchannel was the fastest available commercial network hardware 50 MHz carrier frequency of a 1 mile range. Unix and VAXen needed a device driver for our new supercomputer Center. We had picked up a few spare GE (General Electric) people, these guys had an IBM mainframe bias (this was way before Lisas and Macs and PCs were just getting commercial), a few had a CDC bias (anti-Unix, too). “It will take 6 months to write and test debug a new driver,” said George (name not to be mentioned).So I went on the unix-wizards mailing list/news group (I did not consider myself a wizard) and posted a request: Anyone have a DR-11W driver? The next morning I walked in and tossed a Versatec line printer output. Next Question? George’s jaw dropped. I think Clem Cole gave it to me from his suite at Tektronix. {The typical NASA (but not unique} NIH (Not-Invented-Here) argument was that you could not trust the security of outside source code. No one bothers to read source code.) I recommend Bruce Perens also for his Pixar open source stories.I helped set up UUCP links from LLNL to CSU Stanislaus, Turlock and CSU Fresno (the undocumented -x flag is your friend). That put them on Usenet. The Cal State U. system finally got a clue. Long story.I think the neatest events involved have Ken Thompson visit a few times (I recently put a recent photo of ken on some Quora (company) question), gave a non-Unix related seminar on computer chess (we are still in touch), and Usenix held its first and only supercomputer workshop near CMU in Pittsburgh. There I met Jim Ellis, Usenet’s founder/developer, before he passed away. Jim declared he was a fan of me and FAQs. Had the honor to meet many computer people along the way. I was the “NASA guy”; so few of us at the time. Because of ken and dmr, Ames had 3 pieces of software from the version 6 tape left off: the Bell Labs azel(6) satellite tracker system (you’d think NASA would want this; got a more up to date version from Phil Karn), sky(6)/astro(6) (Bob Morris and ken) an ephemeris (the night sky), and we had Dave Nagel (later to be at Apple and Bell Labs) speak(6) which runs the Vortrax speech synthesizer (I never use). We were the only site outside Bell Labs to run these programs.We had an informal dinner group (based on the food-p mailing list in Berkeley (which came from the Kabuki West mailing list)). We started an informal Usenix self-moderation experiment to see if we could control flame wars using FAQs. We could not. People are just not logical. What you think isn’t how other people think. We did learn the useful reading limit appeared to be 200 lines. People failed to text search. I would move these around when Ames left Usenet. I set up reference servers with DEC for graphics based on Dongarra’s netlib (I was a SIGGRAPH Chair for 2 years; we had a great chapter).I took special active interest in the job hierarchy (misc.jobs.* in the end) for NASA, and for the community. This was why I did the first FAQs. The other NASA Centers were and are largely completely clueless about Usenet (this was how we hired the best talent for the NAS, people didn’t want DOD jobs). The FAQs suggested short things employers wanted in resumes, and things prospective employees wanted. Not perfect, but it had some small effect.I should note that while we had/have inter-Center budget rivalry, for purposes of hiring, I took a Center-neutral view. All NASA Centers needed computer people (retention is the problem; and not all because of money but because of aerospace industry culture).I moderated a discussion group on computer security between NASA Ames and LLNL. I didn’t want to moderate it. I wrote an informal paper for NASA internal use (The Inspector General’s Office). Erik Fair has part of these discussions along with many other Usenet notables (bandy and others). Most notably was a guy having to deal with a KGB agent: Cliff Stoll. I gave the pointer for the CACM paper. I would have known, told him to leave me out of any book, but any cover was blown, but apparently added realism, because of Usenet posts. The most important barely surviving Usenet hierarchy is comp.security.*.In time I was asked to moderate comp.parallel. This enabled me to also keep news.announce.conferences live with cross-posting agreements. Just after UCSC decided to drop news (you know in web browers, you should be able to configure news:newsgroupname and read Usenet), I was invited to join the Big-7/8 board, but I declined.This is a very short version of my Usenet activity (what I can talk about; I need to note there are things that I am not at liberty to talk about).