Senior Statistical Modeler — Pricing & Promotion Optimization

Employer description and requirements

No. of positions: 1

Remote/India, EST overlap 4 hours

Immediate- 1 week availability

Engagement type: Contract

Senior Statistical Modeler — Pricing & Promotion Optimization

Role summary

We're looking for a Senior Statistical Modeler to lead the analytical direction of our pricing and promotion work. This is a hands-on technical leadership role: you'll set the modeling approach, mentor and direct a team of data scientists and analysts, and own the statistical rigor behind our pricing, promotion, and demand decisions. You'll turn large, messy commercial datasets into defensible, business-ready insight — and be able to explain the "why" behind every number to non-technical stakeholders.

Key responsibilities

Set the technical direction and standards for the team across predictive modeling, elasticity estimation, and price/promotion optimization.

Build and oversee price elasticity models and price optimization that translate directly into pricing recommendations and revenue/margin impact.

Lead promotion optimization — measuring promotional lift, efficiency, and ROI, and recommending optimal promo mechanics and depth.

Own substitution and cannibalization analysis to understand cross-product effects of pricing and assortment decisions.

Direct affinity / market-basket analysis to inform bundling, cross-sell, and promotion design.

Model trend and seasonality and build robust demand forecasts at the SKU and category level.

Apply rigorous statistical analysis and inference — hypothesis testing, confidence/uncertainty quantification, experimental and quasi-experimental design (A/B tests, causal inference) — and hold the team to that standard.

Drive data analysis and insight generation, turning model output into clear, actionable recommendations for commercial and executive stakeholders.

Mentor and review the work of junior modelers and analysts; establish reproducible, well-documented modeling practices.

Partner with pricing, category, finance, and product teams to embed models into decision-making.

Required qualifications

Advanced degree (Master's or PhD) in Statistics, Economics/Econometrics, Operations Research, Applied Mathematics, or a related quantitative field — or equivalent experience.

8+ years building statistical and predictive models in a commercial setting, with a substantial track record specifically in pricing and/or promotion optimization.

Deep expertise in: regression and econometric modeling, price elasticity estimation, demand forecasting, time-series methods (trend/seasonality), causal inference, and experimental design.

Hands-on experience with substitution, cannibalization, and affinity/market-basket techniques.

Strong command of statistical inference and the ability to quantify and communicate model confidence and uncertainty.

Proficiency in Python and/or R and SQL; comfort working with large-scale, real-world transactional data.

Deep industry experience in a relevant domain (retail, CPG/consumer goods, e-commerce, or another pricing-intensive sector) — you understand the commercial realities behind the data.

Proven ability to lead and direct a team and to communicate complex statistical results to non-technical business leaders.

Preferred

Experience with commercial pricing/revenue-management platforms or having built such capability in-house.

Familiarity with optimization methods (constrained/mathematical optimization) applied to pricing and promo planning.

Experience operationalizing models into production decision systems and building model-monitoring/validation practices.