Data Scientist Lead

Role Purpose

We areseekinga highly experienced Data Scientist with deepexpertisein Operations Research to join our advanced analytics this role you will lead the formulation and solution of complex optimization and analytical problems across domains such as Supply Chain Retail Telecom and other industries. You will work on large-scale data-driven decision systems combining optimization simulation and machine learning techniques to deliver measurable business impact. The ideal candidate will bring strong algorithmic thinking hands-on modeling experience and the ability to deploy scalable solutions.

Experience Requirements:

10 years ofrelevantexperience in Data Science with strong focus on Operations Research

Proven experience across multiple domains:

Supply Chain (network design inventorylogistics)

Retail (pricing assortment demand planning)

Telecom (network optimization capacity planning)

Hands-on experience solving large-scale optimization problems in production environments

Experience with both exact solvers and heuristic approaches for complex problems

Demonstrated ability to translate business problems into mathematical formulations

Strong stakeholder communication and ability to explain complex models

Experience mentoring teams or leading OR initiatives

Key Responsibilities:

Lead end-to-end design and implementation of Operations Research and advanced analytics solutions across multiple domains.

Formulate real-world business problems into mathematical optimization models.

Develop and deploy large-scale optimization models for:
Supply chain network design inventory optimization routing and scheduling.

Applyappropriate algorithmictechniques (exact heuristic stochastic) based on problem complexity and scale.

Perform simulation and scenario analysis to support decision-making under uncertainty.

Integrate forecasting models with optimization systems.

Collaborate with cross-functional stakeholders to translate business requirements into analytical solutions.

Drive production deployment usingMLOps/Optimization Ops practices.

Mentor junior team members on OR methodologies and best practices.

Qualifications and Skills:

Core Data Science & Technical Skills:

Strong foundationin Data Science Machine Learning and Statistics

Advancedproficiencyin Python (Pandas NumPy SciPy Scikit-learn)

Experience with OR and optimization tools (PyomoPuLP OR-Tools CVXPYGurobi CPLEX

Experience with data engineering (SQL ETL) and cloud platforms is a plus

Deliver

Deep Algorithmic Knowledge (MANDATORY):

Optimization Techniques:

Linear Programming (LP): Simplex Interior Point Methods

• Integer & Mixed Integer Programming (IP/MILP): Branch & Bound Branch & Cut
• Nonlinear Programming (NLP) and MINLP
• Convex Optimization and Duality Theory

Network & Graph Algorithms:

• Shortest Path (Dijkstra Bellman-Ford)
• Max Flow / Min Cost Flow
• Assignment and Transportation Problems

Dynamic & Stochastic Methods:

Simulation Techniques:

Heuristics & Metaheuristics:

Constraint-Based Methods:

Domain-Specific OR Models

Forecasting & Integration
Forecast Optimization integration