Job Description
Responsibilities:
Work on a variety of business applications including but not limited to
Customer Segmentation & 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
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, 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.
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).
8+ years of relevant experience in Data Science with a minimum of 6+ 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.
Demonstrated use of analytical packages and query languages such as SAS, R, SQL, SPSS, Matlab,
Alteryx, Python
Employement Category:
Employement Type: Full time
Industry: Full time
Functional Area: Hospitals
Role Category: Analytics
Role/Responsibilies: Data Scientist
Contact Details:
Company: Novartis Healthcare
Location(s): Hyderabad