Senior Data Analyst

CARFAX•London, ON

9d•Hybrid

About The Position

Join Team CARFAX as a Senior Data Analyst. At CARFAX, we pride ourselves on being mission-focused on helping to grow a brand built on accuracy and integrity. We care deeply about our products and our customers, helping millions of consumers make more-informed decisions every day. We value our teammates as our most valuable asset and promote a balanced life while tackling challenging projects in a fast-paced environment, embodying a 'work-hard, play-hard' culture. Our four-day week continues in Summer 2026. As a Senior Data Analyst, you will collaborate with Data Science and Data Technologies teams to architect analytics solutions for key company products. This role requires a blend of high-level research and technical execution. You will be responsible for the integrity of the data pipeline, identifying high-value inputs, optimizing data flow for production models, and monitoring the real-world performance of our systems. At CARFAX, we believe in the power of teamwork and value in-person interactions, requiring 2 days per week in our London, ON office, subject to change with future business needs.

Requirements

3–7 years of direct experience in advanced data analytics or a Master’s Degree in Statistics, Data Analytics, or a related field.
4+ years’ experience in R/Python and SQL
2+ years’ experience in creating reports and dashboards (Shiny, Quarto, or equivalent).
Solid understanding of statistical modeling techniques such as linear regression, logistic regression, GLM, etc.
A proven track record of handling complex research tasks and managing data-heavy projects from discovery to production.
Ability to effectively communicate analysis and insights to all levels of the organization
A passion for continuous learning and the confidence to challenge the status quo

Responsibilities

Analyze complex, multi-source datasets to identify and validate high-signal inputs for data and model pipelines.
Optimize signal-to-noise ratios by implementing sophisticated logic to curate and refine large-scale datasets for downstream applications.
Perform deep-dive analysis on system health metrics to track model performance and identify optimization opportunities.
Build and maintain interactive dashboards and tools to enable cross-functional product exploration and monitoring.
Translate complex data findings into actionable insights and recurring reports for internal stakeholders to drive strategic decision-making.
Identify and implement automated processes to supercharge data quality and consistency.
Document methodologies and present findings to technical and non-technical audiences, acting as a bridge between data engineering and business logic.