Senior Statistical Modeler - Pricing & Promotion Optimization

Company: WillWare Technologies.

Work Mode: Remote / Contract.

Time Zone: 4 hours of EST overlap.

Role summary:

We are 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 will 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 will 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