Staff Data Scientist, Pricing

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Develop and manage demand and elasticity modeling capabilities across various destinations, durations, data tiers, and customer segments.

• Create machine learning models for demand forecasting and willingness-to-pay, progressing from exploratory phases to production with ongoing monitoring and retraining.

• Construct the optimization layer that translates forecasts and elasticities into suggested pricing, adhering to margin, competitive, and partner constraints.

• Design and evaluate pricing experiments employing statistical rigor, applying causal methods when randomization is not feasible.

• Establish governed definitions for pricing, costs, and package economics within the data ecosystem.

• Collaborate with Commercial and Finance teams to link pricing decisions with margin, revenue, and opportunity sizing.

• Set the analytical benchmarks for pricing, including evidence requirements and validation of models or recommendations.

• Develop analytical capabilities from raw data and business inquiries into frequently utilized commercial tools.

• Relate financial, product, and operational analyses to financial results.

• Convert analytical precision into commercial applications while collaborating closely with Commercial and Product teams.

⛳️ Requirements

• 7+ years of experience in data science, quantitative economics, or applied research, including work in pricing, monetization, or marketplace economics that influenced decision-making.

• Background in dynamic or algorithmic pricing systems currently in operation.

• Advanced degree in Econometrics, Statistics, Operations Research, or a related field, or equivalent practical experience in demand estimation and identification issues.

• Hands-on experience with machine learning throughout the entire lifecycle, from feature engineering and model selection to deployment.

• Knowledge of optimization and decision-science techniques, including constrained optimization, bandits, or reinforcement learning.

• Demonstrated expertise in experimentation, including designing and defending experiments as well as understanding decision frameworks and potential failure modes.

• Experience in building analytical capabilities from raw data and business questions into frequently used commercial tools.

• Strong instincts in data modeling, with experience in creating reusable definitions and establishing single sources of truth.

• Ability to work with financial, product, and operational data, linking analysis to financial outcomes.

• Proficiency in the Python ML stack and strong SQL skills.

• Engineering practices that enable others to run and maintain code effectively.

• Exceptional communication skills, including the ability to articulate methodological arguments clearly.

• Self-motivated with the ability to create structure in ambiguous situations.

• Comfort with utilizing AI tools to enhance analytical efforts.

• Proficient in English for communication during meetings and asynchronous interactions.

🏝️ Benefits

• Full-time, permanent employment.

• Fully remote work arrangement.

• Salary range adjusted in accordance with local market rates and cost of living.

• Equal-opportunity employer.

• Reasonable accommodations available upon request for individuals with disabilities throughout the interview process.