Principal Data Scientist with AI

ArkInfoCubes LLC
India

Principal Data Scientist with AI- Senior Statistical Modeler — Pricing & Promotion Optimization

Remote- India- Contract role

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.

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