Data Scientist

OPENLANE • Full-time • Carmel, IN, US • 3m ago

Who We Are:

At OPENLANE we make wholesale easy so our customers can be more successful.

We’re a technology company building the world’s most advanced—and uncomplicated—digital marketplace for used vehicles.

We’re a data company helping customers buy and sell smarter with clear, actionable insights they can understand and use.

And we’re an innovation company accelerating the future of wholesale remarketing through curiosity, collaboration, and an entrepreneurial spirit.

Our Values:

Driven Waybuilders. We pursue challenges that inspire us to build, create, and innovate.

Relentless Curiosity. We seek to understand and improve our customers’ experience.

Smart Risk-Taking. We transform risk into progress through data, experience, and intuition.

Fearless Ownership. We deliver what we promise and learn along the way.

We’re Looking For:

We are seeking a skilled and curious Data Scientist with a strong background in econometrics, macroeconomic forecasting, and automotive industry analysis. You will join our growing analytics team focused on delivering high-impact insights across pricing, inventory, and market strategy. This role leverages large datasets, advanced statistical modeling, and domain knowledge to support data-driven decisions across wholesale and retail automotive markets. The ideal candidate will have a strong foundation in economic modeling, exceptional analytical thinking, and a passion for translating data into business value.

You Are:

Analytical. You solve complex problems using data and rigorous methods.
Insightful. You connect macroeconomic trends with customer behavior and business performance.
Collaborative. You work closely with cross-functional teams to bring insights to life
Communicative. You translate complex technical findings into clear, visual, and actionable narratives.

You Will:

Develop and maintain econometric models that explain and predict trends in vehicle pricing, inventory turnover, buyer behavior, and macroeconomic impacts.
Conduct causal inference analysis, time series forecasting, and elasticity modeling to support business initiatives in pricing, supply chain, and demand planning.
Monitor and interpret relevant economic indicators, such as interest rates, employment trends, fuel prices, and inflation, and their impact on vehicle sales and valuations.
Collaborate cross-functionally with product, strategy, and data engineering teams to define data needs and integrate insights into business processes.
Present findings to internal stakeholders and executive leadership through clear, visual, and actionable storytelling.
Drive the application of Bayesian methods, panel data analysis, or structural models to inform strategic business scenarios and policy changes.

Who You Will Work With:

Reporting to the Sr. Director of BI, this role will partner with Product Management, Strategy, Engineering, and Market Intelligence teams on a regular basis.

Must Have’s:

BS in Economics, Data Science, Statistics, Engineering, Finance, or related technical field
Strong foundation in econometric techniques and regression based inference (e.g., fixed/random effects, instrumental variables, GMM, discrete choice models).
Proficiency in Python, R, or Stata and experience working with large datasets using SQL or big data tools.
Experience in CICD deployment and model management in Docker / Git / container deployments.
Solid understanding of macroeconomic frameworks, especially in relation to automotive, mobility, or durable goods industries.
Excellent communication skills, with the ability to distill technical insights into clear business narratives.

Preferred Qualifications:

Experience in the automotive sector, wholesale vehicle markets, or transportation economics.
Familiarity with ML methods (e.g., gradient boosting, random forests) as complements to econometric modeling.
Exposure to vehicle pricing, leasing/residual value modeling, or fleet economics.
Experience using BI tools (e.g., Domo, Tableau, Power BI) for data storytelling.

Nice to Have’s:

Master’s or PhD in Economics, Econometrics, Statistics, Data Science, or related field
Experience in the automotive sector, particularly in wholesale vehicle markets or transportation economics
Familiarity with machine learning techniques such as gradient boosting or random forests
Exposure to vehicle pricing, leasing/residual value modeling, or fleet economics
Experience with BI tools like Domo, Tableau, or Power BI for data storytelling

What We Offer:

Competitive pay
Medical, dental, and vision benefits with employer HSA contributions (US) and FSA options (US)
Immediately vested 401K (US) or RRSP (Canada) with company match
Paid Vacation, Personal, and Sick Time
Paid maternity and paternity leave (US)
Employer-paid short-term disability, long-term disability, life insurance, and AD&D (US)
Robust Employee Assistance Program
Employer paid Leap into Service Day to volunteer
Tuition Reimbursement for eligible programs
Opportunities to expand your skill set and share your knowledge across a publicly traded, global organization
Company culture of internal promotions, diverse career paths, and meaningful advancement