Senior Data Scientist

What it’s like to be a Northbridge Senior Data Scientist

The Data Science Team is a central partner to the business for Northbridge’s predictive and prescriptive capability using applied statistics, machine learning or artificial intelligence to build business solutions.

The primary role of the Senior Data Scientist is to lead and implement the data science lifecycle for multiple business use cases, with the objective to improve Northbridge’s customer experience, risk mitigation, underwriting and claims processes. A strong sense of ownership and eagerness to solve high-impact business problems with data science are key traits to success in this role.

Tackle a breadth of challenges from wrangling data, finding the optimal model fit, providing recommendations to business stakeholders, and implementing MLOps with IT Services. Be a part of an entrepreneurial team that balances independence and teamwork to deliver data science solutions.

We want your talent

If you are great at:

• Own the end-to-end data science lifecycle for multiple business use cases, from understanding the business problem, to data extraction and configuration, to model development and evaluation, to production deployment and change management
• Design, oversee and evaluate models from the perspective of statistics, business, operational performance, fairness, regulation, and risk
• Lead discussions with stakeholders to identify business use cases, develop an effective work plan to meet objectives, and provide recommendations to integrate predictions into business processes
• Apply advanced technical skills in data engineering and exploration, statistical modeling and machine learning, and deployment pipelines to effectively solve business problems
• Jointly establish and implement MLOps with IT Services for batch and real-time integration of prediction services

If you have:

• Undergraduate degree in Statistics, Mathematics, Computer Science, or relevant field
• Masters or PhD in Statistics, Mathematics, or Computer Science is an asset
• 4-6 years of professional experience in applied statistics and/or machine learning model development and implementation
• 4-6 years of professional experience in data wrangling and feature engineering, including writing queries to integrate data from multiple sources
• 4+ years of programming experience with SQL and Python/R
• Proficiency in operational procedures, workflow, and processing function

We really mean it when we say we put you first. Here are a few ways how:

• Hybrid work! We have a flexible hybrid model that allows you to work from home up to 2 days per week, with added flexibility for when you really need it.
• We offer competitive salaries and support your financial health through our employee share purchase plan, pension plans, RRSP, discounts on staff insurance, and more!
• We help you prioritize your well-being from day one through flexible health benefits, early leave days, wellness programs, rewards, and recognition programs.
• We are invested in helping you grow in your career through education assistance to complete your CIP, FCIP, CRM or other courses desired, internal mobility, Leadership training and mentoring programs.
• NBFC cares about the community and supports the causes you believe in with donation matching and team volunteer days.

We’re committed to pay transparency and fairness. The base salary range for this role is $100,000–$150,000, reflecting expected base pay — not the total compensation package. Actual base salary may vary depending on your experience, skills, and alignment with the position. We’re also open to candidates at different levels, so if this range doesn’t quite match your expectations, don’t let that hold you back — we’d still love to hear from you.

This is a real opportunity — we’re actively hiring! If the role sounds like a good fit, we encourage you to apply. Beyond base pay, we offer a robust Total Rewards program that includes benefits, wellness support, and other meaningful perks.

We also want to be transparent about our hiring process. While one of our systems includes AI capabilities, over 99% of our screening is done by real people. We believe in thoughtful, human‑centered hiring decisions and are committed to giving every application the attention it deserves.

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