Minimum requirements
What You’ll bring to the role:
• Education: 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.)
• 7+ years of proven 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). Crafting and deploying ML modeling 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: Good command over Python, R, SAS. Strong coding skills with the ability to write high-performance code in Python; exposure to PySpark, Tensorflow. Proficient with SQL and Hive. Exposure to DataIku and UI interface tools like R-Shiny, Streamlit, etc. desirable. Exposure to AWS and ML Pipelines on cloud desirable
