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It is a bit tricky to answer that question directly because what a company considers a "Data Scientist" depends on the nature of work that it is involved in.For simplicity, let's create a binary partition of the data science field and classify the data wizards as either computer scientists or statisticians (in reality, however, a data scientist would be a weighted average of the above two)For example, pure play analytics firms like Fractal Analytics, Mu Sigma, Absolut Data would probably be referring to skilled statisticians with programming knowledge in R, SAS, and at times python, as Data Scientists. Among these, Mu Sigma is in Bangalore and has been growing a rapid pace in the past couple of years. I am not sure about any other pure play firm in Bangalore or Hyderabad.In addition to these are bigger consulting firms like Accenture, EY, KPMG, Deloitte which have some sort of an analytics practice either supporting in-house projects or directly serving external clients. Most of these are looking for people with analytical skills. A list of current opportunities is difficult to put out here but the easiest way to find out is through the job search on LinkedIn.On the other end of the spectrum are companies like Amazon and Facebook, which generally refer to computer scientists with machine learning skills as Data Scientists. They expect a Data Scientist to be very proficient in a low level programming language and a scripting language. I know that many of these companies are looking for Data Scientists since I keep getting updates on glassdoor and LinkedIn. A few that I recently saw were Xerox, Adobe, and Flipkart.Somewhere in the middle of these are companies that support in-house practices like FICO, GE, Genpact, HP, Dell etc.Do note that positions in most companies vary with the team and can be drastically different although the nomenclature has become to write Data Scientist

I was in the same position 2 years back. I made a choice and I am happy about my choiceI completed by B.D.S. in 2013 JuneI like most of my friends was planned to go for M.D.S. most of your professors, mentors, friends will recommend you to go for M.D.SFollowing the crowd, I started preparing for the entrance.The I was acquainted with the truth.My mind was not ready to study for another 9 months and appear for the entrance. Even if I studied hard, mu chances of getting a government MDS seat in Oral Surgery (my preferred subject for MDS) were negligible given my low IQ.My parents had already spent around 6 lac for my B.D.S even after being entitled with partial scholarship form university.I was not in a mood to ask more from my parents even though they were not gonna say no for educational expenses.Hence I started working in a private clinic for a pay of 15,000 per month. After about practicing for 4 months, I felt depressed for being paid so low. Now I partnered with one of our lecturers to run his clinic on 40:60 basis (I would get 60%).I worked in that clinic for about 6 months and again, I was not satisfied with the job.I left the clinic took a vacation on the amount I earned if this brief period of time and freelanced with Indian cancer society.This is the turning point. Even tough I worked them for 4 weeks, I meet with some excellent people. I came to known about the world beyond dentistry and brick and mortar clinics.I was fascinated by the wide spectrum of “PUBLIC HEALTH”I searched, inquired about Masters in Public Health (MPH) and narrowed down my list to get two institutes Tata Institute of Social Sciences, Mumbai, and Public Health Foundation of India, Delhi NCR.But instead of MPH, I opted for MSc in Clinical Research from Public Health Foundation of India.Now I am about to complete my MSc and I am already placed with Tamil Nadu Government Health Ministry as Consultant Research.Well the pay is just enough but the work is satisfying for me.Their are many opportunities after BDS, you need to explore themMasters in Health AdministrationMasters in Public HealthMasters in Hospital ManagementMasters in Clinical ResearchMasters in EpidemiologyMasters in Community MedicineGoogle them and you will get tho know the details.Don’t opt for one year diploma, instead always prefer for 2 years masters. It matersMost important brainstorm on your preferences. Take time, life is too short to correct mistakes.Try opportunities abroad, EU is best for medical research. Some offer scholarships too.Thanks for A2A

Last update December 2015:Several people have produced data and machine learning landscapes.From Shivon Zilis - Machine Intelligence:From Matt Turck:"Analytics" and "big data" include a broad swath of startups. Many startups use big data underneath their applications, of course, but aren't doing anything innovative on the big data front. It's useful to restrict this list to companies that are working with a new technology as well as providing a new form of service.The following are some loose, overlapping categories...For business intelligence, generally more focused on cloud accessibility and ease of use than on data scale:DomoPentahoKognitioQlikTech - not really a startup anymore, but an up-and-comer in this spaceSiSense - thanks to Bruno Aziza belowFor in-database analytics (big data, not traditionally in the cloud, often using columnar database innovations, and lately, Hadoop):Aster DataCalpontParAccel - now underneath AWS's RedShiftGreenplumNetezzaVerticaNotice, this wave of startups have (all but one) been acquired in the last several years... I still consider these late-stage startups even though they're borderline cases.Rather than include a much, much longer list of databases, I'll just refer you here:For advanced analytics (data mining, machine learning, sophisticated modeling, simulation):Continuum AnalyticsDatabricksKNIMEParadigm4PiCloudPLOM.IO - commercialized as Epy.io - beautiful pitch, good cause!Precog - recently acquired by RichRelevanceRevolution AnalyticsSkytreeUforaYhatFrom my perspective at Ufora, interest in tools designed for practitioners of advanced analytics (coders, quants, researchers, analysts, data scientists) is heating up.Regression / classification / graph analysis generalized to accept a company's unique data, sometimes with GUI-driven control and less coding:Alpine DataAlteryxAyasdiBigMLContext RelevantLavastorm AnalyticsNeo Technologytresata* - automated predictive analyticsFor SQL / NoSQL / Hadoop combinations (true big data, large scale data processing, often limited advanced analytics capabilities) in the cloud:ActianDatameerHadaptInktank / CephPlatforaSplice Machine* - "real time SQL on Hadoop"ZettasetDeveloper centric NoSQL/Hadoop tools for managing big data:ClouderaDatastaxHortonworksInfochimpsKarmasphereMapRMortar DataQubole* - "intuitive UI to Hive, Pig, & MapReduce"RainstorSqrrl* - using Apache AccumuloFor search, data visualization, basic data mining, and predictive tools; often using other NoSQL solutions:Centrifuge SystemsDigital ReasoningEdgeSpringLucidWorksPalantir - grown up out of the "startup" phaseTableau - also grown up out of the "startup" phaseTrifacta* - data transformation phase of ETLFor complex event processing:StreamBaseFor real-time dashboards:ChartbeatMetamarketsVisual Revenue... quite a lot more in this categoryInfrastructure for real-time web and mobile:Joyent - Awesome team. Smart engineering. I'm a fan.For new-age spreadsheets:Permanent... + many more. This category is a graveyard centered around Excel and Google Docs.Data resale:DataSiftExversionFactualQuandlTopsyGPUs:SQREAM TechnologiesSpecific VerticalsAd-Tech: demand-side platformsAdchemyAppNexusBRANDSCREENDatXuInvite MediaLucid MediaMediaMathTriggitTurnX+1Ad-Tech: online marketing optimization toolsCoremetricsOmnitureRichRelevanceUnicaBio:AccelrysAffymetricAriadne GenomicsBioXprDNAnexusEagle GenomicsGeneva BioinformaticsIO InformaticsSpiral GeneticsLife TechnologiesTripos Discovery InformaticsEngineering / performance monitoring:Concurix... many more.Finance (with an emphasis on FinTech):Also:1010dataArialyticsQuantConnectQuantopianMarketing:PivotLinkKontagentClarioOther lists of analytics and data startups:42 Big Data Startups - Vote for the Top 10Data startups collection on PinterestBig Data Start-up Funding By VendorMuch to add, including some important ones. If I have an opportunity, I'll continue to extend this list.Some useful blogs and market research, although startups are only a portion of their focus:The Big Data LandscapeKurt Monash: http://www.dbms2.com/Merv Adrian: http://blogs.gartner.com/merv-adrian/James Kobelius: http://blogs.forrester.com/blog/143IDC: http://www.idc.com/Intersect360: http://www.intersect360.com/It's also worth keeping an eye on the established firms, of course... Oracle, SAP (HANA), Microsoft, IBM (SPSS), SAS, MathWorks, MicroStrategy, MarkLogic, TIBCO, etc., and consulting companies like Opera Solutions, Mu Sigma, Accenture. McKinsey is building out an advanced analytics practice.