Manager - Data scientist - Healthcare/Pharma

Your responsibilities include but not are limited to:

- Understand sophisticated business problems from Country/Regional/Global business functions and formulate and deliver an end-to-end data science solution employing statistical and sophisticated machine learning techniques along with functional expertise for generation of actionable insights. Able to use business presentations, smart visualization tools and contextual story-telling to translate findings back to business users with a clear quantified impact

- Support CTS CONEXTS business in building capabilities by involving in various initiatives like knowledge sharing, on-boarding and training support, support in all business-related tasks/activities, building process documentation and knowledge repositories

- Work on a variety of business applications including but not limited to: Customer Segmentation & Targeting, Event Prediction, Propensity Modelling, Churn Modelling, Customer lifecycle management and Lifetime Value Estimation, Recommender Systems, Launch Analytics, Marketing Mix Modelling and Revenue Optimization, Price Optimization

- Quickly learn the use of advances in Data Science tools, techniques and latest technology platforms needed to answer a wide range of critical business questions, Research and co-develop with supervisor new algorithms, methods, statistical models and business models and providing insight into structured and unstructured data

- Collaborate with globally dispersed internal partners and cross-functional teams to solve critical business problems and deliver successfully on high visibility critical initiatives

- Develop automation for repeatedly refreshing analysis and generating insights, Project manage own tasks and works with allied team members; plan proactively, ensures quality of team deliverables, anticipate and actively manage change, set partner expectations as required, identify operational risks and independently drives issues to resolution, minimize surprise partner concerns

- Understand advances in the brand and therapeutic area (drug indication, lifecycle stages, etc.) and various pharma data sources (such as sales, contracting, promotions, social media, claims, Real-World Evidence, etc.) for improving the analytical solution

- Support team leaders in recruitment and on-boarding of new associates within the organization, Participate in various knowledge sharing sessions that enables growth and improves quality of CTS CONEXTS deliverables across the functions, Stay in sync with all internal functional operating procedures like time tracking, critical metric tracking and reporting, and other internal systems and processes.

- Education (minimum/desirable): Post graduate (or Graduate from a premier University) in a quantitative subject area (e.g., Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.)

- Experience: 6+ years of relevant experience in Data Science. Experience in commercial pharma would be an added bonus.

- Technical Skills: Statistical Modelling/Machine Learning: Must have: Statistical and Machine Learning techniques like Regression (esp., GLM, non-linear, etc.), Classification (Trees, Random Forest, Boosting, SVM, CART, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Market mix modelling, Dynamic Programming and Optimization techniques, Recommender Systems, Time Series Forecasting.

- Good to have: Stochastic models, Bayesian Models, Markov Chains, , Deep Learning techniques on structured and unstructured data, Text mining and Natural Language Processing (NLP)

- Data science programming languages and querying databases: R, Python, SAS, SQL/HIVE, Familiarity with Alteryx will be a bonus

- Exposure to UI interface or web-apps building using R-Shiny, Flask, etc, Good to have: Exposure to AWS and ML Pipelines on cloud: Pharmaceutical industry domain/datasets knowledge

- Soft Skills: Storyboarding and Storytelling, Interpersonal and communication skills, Ability to operate effectively in a matrix environment, Strong partner leadership skills, Strong standout colleague who is dynamic and result oriented