Data Scientist Fellow I

This is a unique opportunity to play a key role in developing a next-generation Parts Pricing Engine from the ground up, supporting a diverse portfolio of more than 400,000 SKUs. You'll help shape the analytical methodologies and pricing strategies that influence how we price our products, respond to market dynamics, and drive business performance.

Working collaboratively with teams across Pricing, Product, Finance, and Digital, you'll turn complex data into actionable insights and scalable pricing solutions. You'll also partner with a consulting team through a Build-Operate-Transfer model to help bring innovative pricing capabilities to life.

If you're passionate about leveraging data science to solve complex business challenges, driving innovation, and making a meaningful impact, this is an opportunity to help shape the future of pricing at International Motors!

• Build and own the pricing methodology across a portfolio of 400,000+ SKUs, including price elasticity, product/customer segmentation, price architecture, lifecycle rules, category strategy, and margin guardrails.

• Co-develop pricing strategies and analytical methodologies, establishing recommendation frameworks that can be executed through the pricing engine.

• Translate complex analytical insights into live, tested pricing logic by defining requirements for the Digital team and validating that production behavior aligns with the intended methodology.

• Address complex pricing challenges, including managing a long-tail product portfolio with limited transaction data, pricing across different stages of the product lifecycle, navigating highly competitive markets, and accounting for diverse brand value propositions.

• Maintain and continuously improve pricing measurement methodologies as data quality improves, new data sources become available, and business strategies evolve, using commercial outcomes to inform ongoing enhancements

• Bachelor's degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field and at least 9 years of analytics, data quality or statistical analysis experience
• At least 2 years of lead experience

OR

• Master's degree in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field and at least 5 years of analytics, data quality or statistical analysis experience
• At least 2 years of lead experience

OR

• PhD in Computer Science, Statistics, Data Science/Analytics, Management Information Systems, Mathematics, Natural Science, Economics, Engineering or similar quantitative field and at least 3 years of analytics, data quality or statistical analysis experience
• At least 2 years of lead experience

• Qualified candidates, excluding current employees, must be legally authorized on an unrestricted basis (US Citizen, Legal Permanent Resident, Refugee or Asylee) to be employed in the United States. We do not anticipate providing employment related work sponsorship for this position (e.g., H-1B status)

• Experience in Data Science, with prior pricing experience preferred.

• Demonstrated expertise in price elasticity, segmentation, price optimization, experimentation, or causal inference.

• Strong proficiency in SQL and Python, with the ability to transform raw data into actionable analysis and production-ready logic.

• Experience working with large, complex, sparse, or imperfect product datasets.

• Strong commercial acumen, including the ability to evaluate margins, competitive positioning, and dealer economics to support strategic pricing decisions.

This position offers competitive market-based compensation, along with a comprehensive benefits package designed to support employee wellbeing. You can learn more about the benefits offered for this position by visiting https://careers.international.com/#benefits.The expected salary offered for this position will fall within the stated range, with the final offer based on the candidates' applicable skills, knowledge, and experience.