Job Location: Hyderābād
Job Description
Understand complex and critical business problems from Country/Regional/Global business functions, formulate integrated analytical approach to mine data sources, employ statistical methods, machine learning & deep 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 and divisions (Oncology, GenMeds, Sandoz). Able to use business presentations, impactful visualization of ML results and contextual storytelling to translate findings back to business users with a clear impact. No direct team management.
Your responsibilities:
Your responsibilities include, but are not limited to:
- Customer Segmentation & Targeting, Event Prediction, Propensity Modelling, Churn Modelling, Customer Lifetime Value Estimation, Forecasting, Recommender Systems, Marketing Mix Optimization, Price Optimization
- Be involved in technology research, capability building across newer technologies and tools in Machine Learning ecosystem at scale.
- Design, run and analyze A/B and multivariate hypothesis tests aimed at optimizing customer and patient experience. Also, pick up new skills and technologies necessary on the job .Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively
- Develop automation for repeatedly refreshing analysis and generating insights Collaborate 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.
- Project manage own tasks and works with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required Independently identifies research articles and reproduce/apply methodology to Novartis business problems
- Ability to work independently, demonstrate initiative and flexibility through effective and innovative leadership. Attention to detail and quality focused, excellent interpersonal and communication skills, innovative, and collaborative behaviors & strong “can-do” orientation
- Assist in hiring of new associates for data science roles.
- Comply to all Novartis operating procedures as per legal/IT/HR requirements
EEO Statement
Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.
Minimum Requirements
What You’ll bring to the role:
- 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 including but not limited to Regression (esp., GLM, non-linear, etc.), Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Exploratory Data Analysis, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining and Natural Language Processing (NLP)
- Designing and deploying ML modelling and prediction pipelines
- 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: o Good command over Python, R, SAS o Strong coding skills with the ability to write high-performance code in Python; exposure to PySpark, Tensorflow o Fluent with SQL and Hive o Exposure to DataIku and UI interface tools like R-Shiny, Streamlit, etc. Desirable o Exposure to AWS and ML Pipelines on cloud 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.)
Why Novartis?
769 million. That’s how many lives our products touched in 2020. And while we’re proud of that fact, in this world of digital and technological transformation, we must also ask ourselves this: how can we continue to improve and extend even more people’s lives?
We believe the answers are found when curious, courageous and collaborative people like you are brought together in an inspiring environment. Where you’re given opportunities to explore the power of digital and data. Where you’re empowered to risk failure by taking smart risks, and where you’re surrounded by people who share your determination to tackle the world’s toughest medical challenges.
Imagine what you could do at Novartis!
Commitment to Diversity & Inclusion:
Novartis embraces diversity, equal opportunity and inclusion. We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration, and empowers our people to unleash their full potential.
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to learn more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network.
Job Type: Full-time
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