Lead Data Scientist - Demand Forecasting & Optimization

Job Description

Job Summary

We are looking for an experienced Lead Data Scientist – Demand Forecasting & Optimization to design and develop advanced forecasting and optimization solutions that address complex business problems.

The ideal candidate will have strong expertise in machine learning, demand forecasting, mathematical optimization, Python, and SQL, along with the ability to translate business challenges into scalable analytical and optimization solutions.

This role requires exceptional analytical and logical thinking, strong hands-on technical capabilities, and the ability to independently own data science use cases from problem formulation and model development through validation, deployment, and production monitoring.

Responsibilities

Demand Forecasting & Model Development

• Design, develop, and improve demand forecasting solutions for complex business use cases.
• Build and evaluate time-series, hierarchical, and probabilistic forecasting models.
• Analyze large volumes of business data to identify demand patterns, trends, seasonality, and forecasting opportunities.
• Continuously improve forecast accuracy through experimentation, validation, model tuning, and performance monitoring.

Optimization & Decision Science

• Design and develop mathematical optimization solutions for production environments.
• Translate complex business problems into well-defined optimization models, objectives, variables, and constraints.
• Identify scalable solution approaches for large and computationally complex optimization problems.
• Apply optimization techniques to improve business decisions across planning, forecasting, inventory, and related use cases.

Model Performance & Productionization

• Own forecasting and optimization solutions from problem definition through production deployment.
• Establish appropriate model validation, monitoring, and performance measurement approaches.
• Troubleshoot model performance issues and recommend improvements based on analytical findings.
• Collaborate with engineering and product teams to ensure models are scalable, reliable, and production-ready.

Technical Development

• Develop scalable data science and optimization solutions using Python and SQL.
• Build efficient data pipelines and analytical workflows to support model development and experimentation.
• Evaluate appropriate algorithms, optimization techniques, and solution approaches based on business requirements.
• Maintain high standards for code quality, documentation, reproducibility, and model governance.

Business & Cross-Functional Collaboration

• Work closely with product, engineering, domain, and business stakeholders to understand requirements and translate them into data science solutions.
• Clearly communicate forecasting results, optimization recommendations, model assumptions, and business impact to stakeholders.
• Provide technical guidance on forecasting, machine learning, and optimization approaches.
• Independently drive complex analytical problems while collaborating effectively with cross-functional teams.

Qualifications

• 8–10 years of experience in Data Science, Machine Learning, Demand Forecasting, and/or Optimization.
• Strong understanding of machine learning fundamentals and end-to-end model development.
• Proven hands-on experience with demand forecasting, including time-series forecasting, hierarchical forecasting, and probabilistic forecasting.
• Strong background in mathematical optimization and solving complex business problems using optimization techniques.
• Strong programming skills in Python and SQL.
• Experience taking data science models from experimentation through production deployment and monitoring.
• Excellent analytical, logical reasoning, and problem-solving skills.
• Ability to independently formulate complex business problems and develop scalable analytical solutions.
• Strong communication skills with the ability to work effectively with technical and business stakeholders.

Preferred Qualifications

• Experience with Rust programming language.
• Retail and/or CPG domain knowledge.
• Experience with Genetic Algorithms and other metaheuristic optimization techniques.
• Hands-on experience with optimization solvers such as Google OR-Tools, Gurobi, or IBM CPLEX.
• Educational or professional background in Operations Research.
• Experience applying forecasting and optimization techniques to retail, supply chain, inventory, or planning problems.

What We Offer

• Competitive salary and benefits package.
• Opportunity to work on advanced AI, forecasting, and optimization solutions with significant business impact.
• Exposure to complex retail, CPG, and supply chain use cases.
• Opportunity to solve large-scale forecasting and mathematical optimization problems.
• A collaborative, innovative, and fast-paced work environment.
• Learning and growth opportunities across data science, machine learning, operations research, retail, and supply chain domains.