Data Scientist

Description

Join Team CARFAX as a Data Scientist

Isn't it time you bragged about where you work? At CARFAX, we do, every day. 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. We’re more than just a company: We help millions of consumers make more-informed decisions every day. We know that our teammates are our most valuable asset, and we value a balanced life while tackling challenging projects in a fast-paced environment. We've created the type of company culture where the term, "work-hard, play-hard" isn't just a catchy saying, it's part of the #CARFAXdifference! One last thing: Our four-day week continues in Summer 2026!

As a Data Scientist, you will be key member of the data science team, working on the development of machine learning solutions for new and existing products. You will work collaboratively with data engineers, data mappers and other stakeholders to design, build and scale ambitious machine learning solutions.

At CARFAX we believe in the power of teamwork and value in-person interactions so that we can collaborate and thrive together. The position will require 2 days per week in our London, ON office subject to change with future business needs.

What you’ll be doing:

• Develop, deploy, and maintain machine learning and NLP models used in production systems
• Monitor model performance, data drift, and model health, and support model retraining and improvements
• Contribute to new data science initiatives, particularly in NLP, text processing, and data decoding projects
• Work with large structured and unstructured datasets to build scalable machine learning solutions
• Collaborate with data engineers and product teams to deploy and scale machine learning models in cloud environments
• Apply NLP techniques such as entity recognition, text classification, document processing, and information extraction
• Communicate analysis results, model performance, and insights to stakeholders
• Build reusable tools, processes, and documentation to improve data science workflows and model lifecycle management
• Stay current with new developments in machine learning, NLP, and large language models (LLMs), and evaluate where they may be applied.

To be considered for this role, you will need:

• Master’s Degree in Statistics, Data Science, Computer Science, or a related field
• 4+ years of experience in SQL/Spark, R, Python
• 4+ years of Experience building and applying machine learning or NLP models to business problems
• Strong understanding and practical experience with machine learning techniques such as regression, tree-based models, ensemble methods, and neural networks, with experience applying these methods to large, real-world datasets and production systems
• Experience working with production machine learning systems, including model monitoring, performance tracking, and model improvements
• Experience with NLP techniques such as Named Entity Recognition (NER), text classification, sentiment analysis, tokenization, or information extraction
• Experience working with large datasets and distributed data processing frameworks (e.g., Spark)
• Experience with cloud platforms (AWS, GCP, or Azure)
• Ability to work independently, prioritize tasks across multiple projects, and contribute new ideas and initiatives.
• Passion for continuous learning and improving data science processes.

What’s in it for you: