Job Description :

We are looking for an experienced Associate Lead Data Scientist (ALDS) with a strong foundation in Machine Learning, Operations Research, Optimization, and Advanced Analytics.

The ideal candidate should have hands-on experience solving complex business problems using optimization techniques such as Mixed Integer Linear Programming (MILP), Constrained Programming, and Non-Linear Programming, along with expertise in modern machine learning and cloud technologies.

This role involves a combination of hands-on technical contribution, client engagement, project ownership, team mentoring, and solution design across domains such as Retail, Consumer Goods, Pharma, Banking, and Insurance.

Candidates with experience in Trade Promotion Optimization (TPO), Revenue Growth Management (RGM), pricing optimization, supply chain optimization, or commercial analytics will be highly preferred.

Mandatory Skills : Operations Research & Optimization

Strong academic and practical background in Operations Research (OR) and optimization. Hands-on experience with :

- Mixed Integer Linear Programming (MILP)

- Mixed Integer Programming (MIP)

- Constrained Programming

- Non-Linear Programming (NLP)

- Mathematical optimization and simulation techniques

Experience using optimization tools such as Gurobi, CPLEX, OR-Tools, Pyomo, and other optimization frameworks.

Trade Promotion & Revenue Management (Preferred)

Experience in one or more of the following : Trade Promotion Optimization (TPO), Revenue Growth Management (RGM), Pricing Optimization, Promotion Effectiveness, Demand Forecasting, Assortment Optimization, or Supply Chain Optimization.

Programming & Data Engineering

Strong programming expertise in Python, SQL, R, NoSQL, and Spark / PySpark. Experience with cloud platforms : AWS, Azure, GCP.

Python Libraries & Frameworks

Hands-on experience with NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, BERT, Scapy, and Scrapy.

Machine Learning & Statistics

Strong understanding of statistical analysis and hypothesis testing, predictive modelling, feature engineering, and model evaluation. Experience with algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, Neural Networks, K-Means Clustering, PCA, and Ensemble Models.

Key Responsibilities :

- Design and develop machine learning, optimization, and analytics solutions for complex business problems.

- Build mathematical optimization models using MILP, constrained programming, and non-linear programming techniques.

- Develop scalable predictive and prescriptive analytics solutions.

- Engage with clients to understand business challenges and convert them into analytical solutions.

- Lead end-to-end AI and analytics engagements, guide and mentor junior data scientists, and conduct project planning and delivery management.

- Define analytics roadmaps, support pre-sales, and contribute to internal accelerators and assets.

Preferred Domain Experience :

Retail, Consumer Packaged Goods (CPG), FMCG, Pharma, Banking, Insurance, Supply Chain, and Revenue Management.