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Added 3 mins ago
Business Analyst - FIN
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Hyundai Capital Canada

Remarketing Analytics Associate

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 5, 2026
Posting language: English
Posted: Oct 6, 2026

Original job description

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, Power BI, Python visualization libraries, or similar tools.

Education:

Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Data Science, or a related discipline.
Strong academic or project experience in Python, analytics, statistics, machine learning, forecasting, data visualization, or related quantitative methods preferred.

Knowledge, Skills & Abilities:

Ability to learn business context quickly, collaborate with stakeholders, and use data to support reporting, forecasting, modelling, and operational decision-making.
Conceptual thinking and problem solving
Communication and teamwork skills with internal customers
Proficiency using MS Office (Word, Excel, PowerPoint)
Ability and desire to learn and constantly improve
Deep working knowledge of Python, including common data and modelling libraries such as pandas, NumPy, scikit-learn, matplotlib, seaborn, or similar tools.
Preferred proficiency in Tableau for dashboard design, visual storytelling, self-service reporting, and stakeholder-facing performance views.
Strong interest in modernizing analytics processes through automation, reusable code, improved data pipelines, forecasting, and scalable reporting solutions.
Ability to clearly communicate insights and drive results. A strong bias towards action.

[Location Update] Effective June 2027, Hyundai Capital Canada’s head office will be relocated from downtown Toronto to the Airport Corporate Centre in Mississauga.

Hyundai Capital Canada Inc. is committed to acknowledge applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.

This posting is for an active, existing vacancy. Hyundai Capital Canada is currently hiring for this role and applications are being reviewed as part of a live recruitment process.

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More about this job

Responsibilities

Analyze and prepare data for recurring and ad hoc reporting, pricing, forecasting, and remarketing decisions, while maintaining and improving dashboards, reports, and data pipelines. Support model and experiment enhancements, investigate data or reporting issues, analyze used-vehicle market trends, and communicate practical recommendations to stakeholders.

Requirements

The role is intended for an early-career candidate with up to two years of related experience, including internships, academic projects, or portfolio work, and a bachelor’s degree in a quantitative discipline. Candidates should have strong Python skills, familiarity with SQL and analytics methods, and preferably experience with Tableau or similar visualization tools.

Skills

Python
SQL
Tableau
Data Analysis
Data Preparation
Data Quality
Forecasting
Statistical Analysis
Model Development
Dashboard Development
Data Visualization
Pricing Analysis
Market Trend Analysis
Automation
Stakeholder Communication
Problem Solving

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Excel
Tableau
Power BI
Pandas
NumPy
Scikit-Learn
Matplotlib
Seaborn
Data Analytics
Business Intelligence
Data Science
Data Preparation
Data Quality
Data Pipelines
Dashboarding
Reporting
Forecasting
Statistical Analysis
Machine Learning
Model Development
Pricing Models
Back-Testing
Vehicle Remarketing
Automotive Finance
Used Vehicle Market
Data Visualization
Process Improvement
Self-Service Analytics

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