Data Scientist - Pricing

Job Summary

Responsibilities

Advising on analysis and modeling techniques, selecting the best fit for structured & unstructured, complex data, and developing custom analytics models to generate insights that drive value for our customers and unlock competitive advantage for our organization.

Collaborating with our analytics engineers to gather the right information from various sources so that you can implement advanced statistical methodologies and design interventions to optimize our business performance.

Conducting exploratory analysis including hypothesis testing, statistical inference, and statistical analysis (predictive and/or prescriptive).

Partnering with business and technical stakeholders to translate challenging retail business problems into state-of-the-art data science solutions.

Developing processes and tools that monitor, analyze and continuously improve model performance and data accuracy.

Working with other data scientists to design and implement experiments and glean actionable insights from experimental analyses.

Defending and explaining the validity of predictive/ML models to those without a background in data science or statistics.

Actively researching new tools and technologies, staying on top of analytics news and best practices.

Qualifications

• Minimum 2 years experience applying data science to pricing and demand problems in ecommerce, retail, or foodservice environments.
• Proven ability to build and analyze price response curves or similar models to identify optimal pricing across a wide range of products.
• Experience using data to inform pricing strategy and day-to-day pricing decisions, even if not the final decision owner.
• Strong understanding of price elasticity, demand forecasting, and trade-offs between margin, volume, and customer acquisition.
• Demonstrated ability to identify strategic low-priced items that drive customer traffic, alongside optimizing prices for both low and high AOV products.
• Comfortable working with large SKU catalogs and messy real-world data to deliver actionable pricing insights.
• Ability to partner closely with merchants, and other teams to translate model outputs into business decisions.
• Advanced Python and SQL skills