Job Description:

Title: Data Scientist

Location: Remote - Canada

Reports to: Director, Data Insights - Product & Technology

Vacancy: Existing vacancy

The Role:

As part of the Valuation Services division of JD Power, you will work to understand what features drive a vehicle's price and run processes to predict future values. Our data science team is accountable for every data point we output and provides industry-leading, accurate, transparent analytics. We are looking for a Data Scientist who will be free to use the latest technologies to solve challenging problems, create innovative processes from the ground up, deploy them into production on our AWS server, and develop the tools for monitoring them. We are a mature and tight-knit data science team looking to add another top-shelf team member ready to make a difference in the automotive industry.

The Impact You Will Have in This Role:

We make data products and every new data product we output will solve a problem in the auto industry. Every Data Scientist will participate in developing and deploying processes and pipelines that go into production and directly impact our core products.

What You'll Be Doing in This Role:

• Daily immersion in automotive industry data
• Development and documentation of multiple critical production processes
• Maintain and iterate on production algorithms, optimizing ETLs and troubleshooting as necessary to handle changing data and valuation requirements
• Collaborate closely with technology and engineering teams to build out new processes and improve existing ones
• Create visual reports in Tableau for data review and validation that will be used by internal and external clients to summarize findings
• Perform extensive QA on internally developed automotive industry forecasts and the resulting vehicle values
• Team environment that encourages the sharing of ideas to build the best predictive algorithms
• Work directly with internal stakeholders to help them understand our predictive products and methodology
• Create decks to make highly technical predictions relatable to the automotive industry
• Ad-hoc data analysis and reporting

Qualifications of this Role:

• Curiosity and passion for solving problems with data
• Great attention to detail and a focus on organization, logic, and data and code quality
• 2+ years of professional experience working with large datasets
• 2+ years of professional experience with statistical programming software (Python/Pandas required, Spark preferred)
• 2+ years of professional experience with database software (SQL, RedShift, Hive, MYSQL)
• Experience working with AWS tools (S3, Sagemaker, Glue, Lambda...)
• Ability to communicate technical processes to both peers and a lay audience
• Master's Degree in Statistics, Data Science, Economics, or a related field

Nice to Have:

• Experience with automotive market data
• Expertise deploying CI/CD with cloud-based systems, managing code in Git
• Experience with Tableau for data visualizations
• Experience with prompting and implementing generative AI output into workstreams
• Some shareable examples of production data pipelines, product deployments, or data visualizations you have created
• Experience deploying machine learning models into production with an API

The Hiring Manager says:

We want data science candidates who can think through a customer journey and an industry thoroughly, creatively and intuitively to understand, explain, and predict issues that have not yet been resolved (in large part because they are only emerging). We need the capability to leverage the right data sets from an impressive set of data assets and to collaborate with others to plan process improvements, optimizations, and data QA.

This position has a starting salary range of $85,000 -$90,000 CAD per year. This is the range we reasonably and in good faith expect to pay for the role at the time of posting. An employee's pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location.