Major Accountabilities Work on a variety of business applications including but not limited to: - Customer Segmentation &amp; Targeting, Event Prediction, Propensity Modelling, Churn Modelling, Customer Lifetime Value Estimation, Forecasting, Recommender Systems, Modelling Response to Incentives, Marketing Mix Optimization, Price Optimization - Develop automation for repeatedly refreshing analysis and generating insights - Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives - Understand life science data sources including sales, contracting, promotions, social media, patient claims and Real World Evidence - Quickly learn the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions - Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively - Manage own tasks and works with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and independently drives issues to resolution, minimizes surprise escalations - Independently identifies research articles and reproduce/apply methodology to Novartis business problems - Has high learning agility and diligently follows updates in industry and area of work Key Performance Indicators - Quality of insights generated and solutions provided, with quantified business impact / ROI - Effective communication with PLS and Country/Regional/Global stakeholders - Executes agreed targets for self - Define and execute development plans for potential Subject Matter Experts - Find creative ways to build team capabilities and play a direct role in driving a culture of innovation - Values and Behaviours: in line with leadership standards of Organization Ideal Background : Education: - (minimum/desirable) PhD or Masters (or Bachelors from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.) - Experience - 7+ years of relevant experience in Data Science. In case of PhD, 5+ years post qualification experience. Experience in commercial pharma would be an added bonus. - Extensive experience required in: Statistical and Machine Learning techniques like Regression (esp., GLM, non-linear, etc.), Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining and Natural Language Processing (NLP) - Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization techniques, Deep Learning techniques on structured and unstructured data, Recommender Systems (content and collaborative filtering), etc. - Tools and Packages: SAS, R, Python, SQL. Exposure to a dashboard or web-apps building using Qliksense, R-Shiny, Flask, etc. would be added advantage

Hyderabad

Data Science Role - Pharma - PhD 

Data Science Role - Pharma - PhD  ,Job Description for Data Science Role - Pharma - PhD  in Upgrade HR Consulting Pvt Ltd in  Hyderabad for (7-12) years of experience. Apply Now!

Job Description for Data Science Role - Pharma - PhD  in Upgrade HR Consulting Pvt Ltd in  Hyderabad for (7-12) years of experience. Apply Now!