We are looking for a Senior Data Scientist to join our data team. This position is responsible for day-to-day operations of pricing and monetization analytics, supporting other team members to achieve unit objectives.

Key Responsibilities

• Lead end-to-end data science projects, translating complex business and product questions into well-defined analytical problems and metrics.
• Conduct advanced exploratory data analysis to uncover hidden patterns, risks, and strategic growth opportunities.
• Develop, validate, and deploy predictive machine learning models in production, specifically focusing on demand forecasting and price optimization.
• Estimate price elasticity and willingness-to-pay across various segments to deliver actionable pricing and promotion recommendations.
• Design and implement mathematical price optimization approaches that effectively balance revenue, margin, and volume constraints.
• Measure the impact of promotional actions, lift, and cannibalization using advanced causal inference methods (e.g., difference-in-differences, synthetic control).
• Design, execute, and interpret controlled experiments (A/B testing) and randomized price/promotion experiments.
• Build reliable data pipelines, analytical datasets, and decision-support dashboards using Python to empower commercial teams.
• Review analytical work across the department, providing technical guidance and mentorship to less-experienced team members.
• Drive the continuous improvement of internal data science processes, modeling standards, and analytical rigor.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, Physics, or a related quantitative discipline.
• At least 4 years of professional experience in data science, statistical analysis, or applied machine learning roles.
• Advanced proficiency in Python for data analysis, modeling, and visualization.
• Strong foundation in statistical inference, experimental design, causal inference, and model evaluation techniques.
• Experience with pricing, demand modeling, elasticity estimation, or revenue/margin optimization.
• Demonstrated ability to independently drive analytical projects in environments with incomplete or evolving requirements.
• Experience communicating analytical findings clearly and effectively to technical and non-technical stakeholders, including translating pricing analysis into commercial recommendations.
• Strong collaboration skills and a high standard of analytical quality and documentation.

Preferred Qualifications:

• Experience with advanced mathematical or probabilistic modeling (e.g., Bayesian hierarchical models for elasticity or demand).
• Demonstrated experience designing and analyzing randomized controlled experiments, including pricing or promotion experiments.
• Familiarity with optimization methods (linear/nonlinear programming) applied to pricing or resource allocation.
• Familiarity with recommender systems or personalization problems, including personalized or segment-level pricing.
• Experience with adaptive experimentation methods, such as multi-armed bandits, including their application to dynamic pricing.
• Domain experience in retail, e-commerce, FMCG, or marketplace environments.