Remarketing Analytics Associate

Who We Are

Hyundai Capital Canada (HCCA) is the Canadian captive finance business for Hyundai Motor Group. We go to market under the service brands Hyundai Motor Finance, Kia Finance and Genesis Finance. Through a network of over 450 Hyundai and Kia dealerships and 30 Genesis distributors nationwide, we provide indirect vehicle financing and leasing solutions to consumers and commercial customers.

Employee Value Prop and Culture

Our employees contribute every day to a culture that is fast-paced, dynamic, energized, agile, and collaborative. From our employee programs to the unique design of our offices, we strive to create a connected, fun, positive, and rewarding workplace where employees feel appreciated, proud of their company, and deeply invested in HCCA’s success.

Global One Company

Many countries. One identity. Hyundai Capital has offices around the world, including South Korea, the United States, China, the United Kingdom, Germany, and Brazil. Our work environments follow consistent themes that represent our global values: simplicity, collaboration, symmetry, and elements of nature.

Position Details

The Associate will support Remarketing analytics by maintaining dashboards and reports, improving data processes, and contributing to reporting, forecasting, and modelling enhancements. This role is well suited for an early-career analyst or recent graduate with a strong quantitative background, advanced Python skills, and an interest in applying data and analytics to business problems. The Associate will use Python, SQL, Excel, and visualization tools such as Tableau to extract, clean, validate, analyze, and present data from multiple sources. The role will also support recurring and ad hoc reporting, data quality reviews, forecasting analysis, model development, and the delivery of clear insights to business stakeholders. Automotive finance or vehicle remarketing experience is an asset but not required.

Duties and

Responsibilities:

• Analyze and fulfill recurring and ad hoc Remarketing data and pricing requests by extracting, cleaning, validating, and interpreting data from multiple sources, including internal sales history, vehicle attributes, condition, mileage, channel performance, and external market data. Use Python, SQL, and related tools to automate repeatable data preparation, conduct data quality checks, support pricing model inputs, and deliver accurate outputs that support operational, pricing, forecasting, and strategic decision-making.
• Support, maintain, and enhance Remarketing Tableau dashboards, recurring reports, pricing performance views, and supporting data pipelines. Monitor data quality and reporting performance, reconcile discrepancies, document reusable reporting logic, and develop self-service analytical tools that provide clear insights into operating results, sales performance, pricing drivers, model outputs, price-to-sale variance, floor price achievement, conversion rate, days to sell, and performance by channel and vehicle segment.
• Develop measurement frameworks and provide analytical support for experiments, program pilots, challenger analysis, pricing model enhancements, and process improvement initiatives. Apply appropriate statistical techniques, assist with feature development, calibration, back-testing, and performance trend reviews, and translate findings into practical recommendations that improve pricing accuracy, forecasting, reporting, and business outcomes.
• Analyze local, national, and broader used vehicle market trends, including supply, demand, depreciation, seasonality, regional performance, and relevant economic or industry factors that impact vehicle values, remarketing strategy, and sales outcomes. Identify patterns, risks, and opportunities that can inform pricing adjustments, forecasting, market-aligned valuation, and strategic recommendations.
• Diagnose issues affecting Remarketing data tools, dashboards, reports, pricing outputs, and model performance by using SQL, Python, and other analytical methods to investigate discrepancies, trace data lineage, identify root causes, and coordinate with business and technical partners on sustainable solutions. Analyze cross-functional Remarketing processes and recommend improvements that increase pricing accuracy, reporting consistency, transparency, automation, governance, and operational effectiveness.

Work

Experience:

• Entry-level to 2 years of related experience, including internships, co-op placements, academic projects, portfolio work, or early-career experience in data analysis, business intelligence, analytics engineering, or data science.
• Practical experience using Python for data preparation, automation, analysis, forecasting, modelling, or visualization.
• Preferred experience developing dashboards, reports, or data visualizations using Tableau, Pow