Role & responsibilities
- Apply advanced forecasting methodologies to estimate sales and revenue for newly launched and pipeline pharmaceutical products (Demand Forecasting good to have skills).
- Incorporate financial modelling and corporate finance principles into forecasting frameworks to support long-term strategic planning.
- Develop robust, data-driven models that incorporate market dynamics, patient behavior, and competitive intelligence to generate accurate and actionable forecasts.
- Collaborate cross-functionally with marketing, commercial, and research teams to ensure alignment of forecasts with strategic objectives and product positioning.
- Leverage statistical, machine learning, and deep learning techniques to uncover insights that inform launch strategies and optimize product performance.
- Partner with key business stakeholders to identify, scope, and execute predictive analytics initiatives that address critical business needs and deliver measurable value.
- Maintain a strong understanding of the pharmaceutical landscape from financial operations to commercialization to provide objective, data-driven input into strategic decisions.
- Collaborate within the analytics team, openly sharing knowledge and seeking feedback to enhance the quality and impact of analytical deliverables.
- Stay current with emerging techniques and tools in predictive analytics, ensuring methodological rigor and adaptability in approach.
- Work comfortably with varied data sources and types, ensuring seamless integration and analysis across structured and unstructured datasets .
Preferred candidate profile :
o Masters or Bachelor in Statistics, Economics, Data Sciences, Engineering, or quantitative related field.
o Minimum of 5 years of working experience as a Data Scientist in industry.
o Deep and broad knowledge of Data Science methods and tools including Simulation model building principles, Machine Learning, and best practices :
o Point Forecasting and Probabilistic Forecasting.
o Agent-based Simulation Model using Anylogic.
o Any type of simulation model experience (Good to have).
o Statistical Forecasting : ARIMA, THETA, Exponential Smoothing
o ML-based Forecasting : GBM, LightGBM, XGBoost, Linear Regression
o DL-based Forecasting : DeepAR, NBEATS, LSTM, RNN
o Hierarchical Forecasting
o Cross-Validation : Rolling-window, Expanding-window, K-fold, Hold-out
o MLOps is also good to have skills.
o Exposure to LLM or GPT good to have skills.