We’re looking for a highly analytical and business-savvy Senior Pricing Data Scientist to join our Pricing Strategy team. In this role, you’ll design and execute advanced pricing models, lead experimentation efforts, and uncover insights that power monetization and growth. You’ll work cross-functionally with Product, Analytics, Revenue, and Engineering to ensure our pricing strategies are data-driven, rigorously tested, and aligned with customer value.
This is a high-impact opportunity for someone who thrives at the intersection of data science, economics, and strategy , and who is passionate about using data to influence pricing, product design, and long-term business outcomes.
Design, build, and maintain pricing and demand elasticity models using statistical and machine learning methods.
Leverage behavioral, transactional, and marketplace data to optimize price points, discount strategies, and product bundling.
Develop tools to support scenario modeling, revenue forecasting, and price testing simulations.
Design A/B and multivariate experiments to test pricing changes, discount strategies, and offer configurations.
Analyze test results with statistical rigor, including significance testing, confidence intervals, and causal inference techniques.
Partner with experimentation platform owners to automate and scale pricing experiments across channels and customer segments.
Conduct in-depth analyses of customer willingness to pay, price sensitivity, and competitor pricing strategies.
Deliver insights on monetization opportunities, marketplace dynamics, and revenue optimization levers.
Partner with strategy and product teams to develop recommendations based on model outputs and empirical evidence.
Collaborate closely with Product Managers, Engineers, and Revenue teams to embed pricing intelligence into user experiences.
Translate complex technical findings into actionable business recommendations for stakeholders across the org.
Contribute to roadmap planning, strategic decision-making, and post-launch pricing reviews.
5+ years of experience in data science, pricing analytics, or quantitative strategy roles.
Advanced proficiency in Python or R, SQL, and statistical modeling techniques.
Strong experience with A/B testing frameworks and causal inference methods (e.g., regression, matching, difference-in-differences).
Solid understanding of pricing theory, elasticity modeling, and optimization.
Excellent problem-solving and critical thinking skills; able to distill ambiguity into structured analyses.
Business-oriented mindset with the ability to prioritize impact and communicate clearly with non-technical audiences.
Self-starter with a passion for experimentation and continuous improvement.
Degree in Data Science, Statistics, Economics, Applied Mathematics, or a related quantitative discipline (Master’s or PhD preferred).
Experience in a consumer-facing marketplace, e-commerce, or SaaS environment.
Familiarity with tools such as Looker, Amplitude, dbt, or in-house experimentation platforms.
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