Manager, Data Science - Pricing and Forcasting

Best Buy•Richfield, MN

13d•Hybrid

About The Position

As a Manager - Pricing and Forecasting Data Scientist at Best Buy Ads, you'll be at the forefront of building and deploying sophisticated data models that drive our retail media network's pricing strategies and inventory forecasting capabilities. This role combines advanced statistical modeling with practical business application, requiring you to create, validate, and productionize models that directly impact revenue optimization. You'll transform complex data into actionable insights, partnering with sales, yield, product, and ad operations teams to enhance decision-making across the advertising ecosystem. This role is hybrid, with preference for candidates in our Richfield, MN or New York City location . You will work some days in the office and some days virtually from home or another non-Best Buy location.

Requirements

Master's or PhD in Statistics, Economics, Computer Science, Operations Research, or related quantitative field.
5+ years of experience building and deploying data science models in production environments.
4+ years of hands-on experience with SQL, Python, and Google Cloud Platform for data analysis and model development.
3+ years of experience with DBT or similar data transformation tools for building reliable data pipelines.
3+ years of experience in display advertising and retail media networks, with a deep understanding of programmatic advertising ecosystems.
3+ years of experience developing dynamic pricing and supply/demand forecasting models specifically in AdTech or related industries
Strong track record of working independently and demonstrating resourcefulness in solving complex technical problems.

Nice To Haves

Experience with dashboard development using Tableau, Looker, or similar visualization tools to communicate model outputs and insights.
Strong ETL skills with experience building end-to-end data pipelines from raw data to production-ready models.
Experience with time series forecasting, demand modeling, and price elasticity estimation.
Familiarity with experimentation frameworks and causal inference methods
Publications or presentations at industry conferences related to pricing, forecasting, or retail media.
Experience translating complex statistical concepts into business recommendations for non-technical stakeholders.
Proven ability to manage multiple projects simultaneously while maintaining high-quality standards.

Responsibilities

Design, develop, and implement advanced pricing models that optimize revenue across onsite and offsite channels, incorporating dynamic pricing strategies based on supply and demand signals.
Build sophisticated forecasting models to predict inventory availability, demand patterns, and revenue opportunities across display advertising channels.
Validate and productionize data science models, ensuring scalability, reliability, and continuous improvement through A/B testing and performance monitoring.
Create and maintain comprehensive business and product metrics that measure advertising performance, yield optimization, and pricing effectiveness.
Leverage metrics and model outputs to generate actionable insights and recommendations for sales, yield management, product, and ad operations teams.
Develop automated pipelines using DBT and Google Cloud Platform to ensure models run efficiently and deliver insights in real-time.
Partner with engineering teams to integrate pricing and forecasting models into production systems and decision-making workflows.
Partner will product team to provide dashboard requirements and wireframes.
Lead model documentation, performance tracking, and knowledge sharing to ensure transparency and reproducibility of data science work.