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.

Where you can work

This role is 100% remote: you can work from anywhere in the world.