Data Scientist I

Key Skills

Data science techniques, Data structuring, Data Visualization, Deep Learning, Python Programming, R Programming, SAS, SQL

Job Description

About the Role:

Understand complex and critical business problems from Country/Regional/Global business

functions, formulate integrated analytical approach to mine data sources, employ statistical

methods and machine learning algorithms to discover actionable insights and automate process for

reducing effort and time for repeated use. High agility to be able to work across various business

domains (commercial, NTO, GDD,NIBR, NBS) or divisions (Onco, GenMeds, Sandoz). Able to use

business presentations, smart visualization tools and contextual story-telling to translate findings

back to business users with a clear impact. No direct team management.

Key Responsibilities:

• Work on a variety of business applications including but not limited to:

o 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.
• 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

Diversity & Inclusion / EEO

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Minimum Requirements

Essential Requirements:

Education

• PhD or Masters (or Bachelors from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathemat ics, Computer Science, Bioinformatics, Ops Research, etc.)

Experience:

• 7+ years of relevant experience in Data Science. In case of PhD, 4+ 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
• Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization techniques, Deep Learning techniques on structured and un structured data, Recommender Systems (content and collaborative filtering), etc.
• Tools and Packages: SAS, R, Python, SQL. Exposure to dashboard or web-apps building using Qliksense, R-Shiny, Flask, etc. would be added advantage.

Why Novartis: Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture

You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards