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| Job Location | Hyderabad |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | Medical / Healthcare |
| Functional Area | DBA / Datawarehousing |
| EmploymentType | Full-time |
Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives Understands life science data sources including sales, contracting, promotions, social media, patient claims and Real World Evidence Quickly learns the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions Articulates solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively Project manages own tasks and works with allied team members; plans proactively, antici-pates and actively manages change, sets stakeholder expectations as required, identifies oper-ational risks and independently drives issues to resolution, minimizes surprise escalations Independently identifies research articles and reproduce/apply methodology to Novartis busi-ness problemsMinimum requirements Masters (or Bachelors from a top Tier University) in a quantitative discipline (e.g. Applied Mathematics, Computer Science, Bioinformatics, Statistics; can also consider Ops Research, Econometrics). 5+ years of relevant experience in Data Science with a minimum of 5 years post qualification experience (PhD considered as experience) Extensive experience in Statistical and Machine Learning techniques like Regression (Linear/Logit/Gamma), Clustering (K-Means/Modes/Hier), Decision Trees, Text Mining and Natural Language Processing, Stochastic models, Bayesian Models, Markov Chains, Monte Carlo Simulations, Non-linear Time Series, Dynamic Programming and Optimization techniques, Design of Experiments, Neural Networks, Statistical Inference, Collaborative Filtering, Feature Engineering, etc. Extensive experience in working with large-scale datasets (in bigdata architecture, data lake, data mart, data warehouse). Demonstrated use of analytical packages and query languages such as SAS, R, SQL, SPSS, Matlab, Alteryx Experience in Big Data platforms like Hadoop eco-system (i.e. Hive,Pig, Sqoop, Mahout), other large scale computing systems ,
Keyskills :
machine learningpythondata analysissqlanalyticsdesign of experimentsnatural language processingbig datatext miningtime seriessocial mediamonte carlo