Principal Data Scientist (Automotive)

TL;DR

Principal Data Scientist (Automotive): Building and optimizing machine learning models to predict vehicle values and drive industry-leading analytics with an accent on advanced feature engineering and production deployment. Focus on creating innovative ML processes, managing end-to-end data pipelines on AWS, and collaborating with product teams to solve complex automotive industry challenges.

Location: Must be based in the USA or Canada

Salary: $130,000–$150,000 CAD / $155,000–$195,000 USD per year

Company

A global leader in data analytics and consumer intelligence, providing proprietary insights and solutions for the automotive industry.

What you will do

• Develop and deploy innovative machine learning models into production environments.
• Collaborate with engineering teams to build and monitor scalable data pipelines on AWS.
• Lead strategic planning and decision-making for data science initiatives.
• Create technical reports and visual dashboards in Tableau for internal and external stakeholders.
• Document machine learning processes and communicate technical findings to non-technical audiences.
• Mentor team members and contribute to the development of predictive algorithms.

Requirements

• 8+ years of professional experience working with large datasets.
• 8+ years of experience with statistical programming (Python, Spark, or R).
• 8+ years of experience with database software (SQL, RedShift, Hive, or MySQL).
• Master’s degree in Statistics, Data Science, Economics, or a related field.
• Proven ability to communicate complex technical processes to a lay audience.
• Must be authorized to work in the USA or Canada.

Nice to have

• PhD in Statistics, Data Science, Economics, or related field.
• Professional expertise in deploying cloud-based MLOps systems.
• Experience with AWS tools such as SageMaker, Glue, Batch, or Lambda.
• Prior experience working with automotive market data.

Culture & Benefits

• Opportunity to work as a full-stack data scientist in a mature, tight-knit team.
• Focus on innovation, collaboration, and data-driven decision-making.
• Exposure to high-impact projects that directly influence the automotive industry.
• Commitment to a diverse and inclusive workforce.