Sr. Data Scientist

About Borrowell

At Borrowell, we’re on a mission to help Canadians feel confident about their money. We empower individuals to take control of their financial futures by providing the tools and insights needed to understand, build, and use their credit effectively.

1 in 10 Canadians use Borrowell for comprehensive credit monitoring and personalized insights. Our innovative services, including Credit Builder and rent reporting, help consumers build credit so they can unlock access to a wider range of financial products at more competitive rates. Additionally, we offer personalized financial product recommendations from Canada’s most trusted providers based on each member’s credit profile and financial goals.

Our team is diverse, inclusive, and driven by a shared passion for making a meaningful difference in the lives of Canadians. We pride ourselves on fostering a culture of collaboration, humility, and innovation. If you’re looking to join a company that’s transforming the financial landscape and empowering Canadians to achieve their financial aspirations, we invite you to explore career opportunities ether, we can help Canadians feel confident about money.

As a Senior Data Scientist
, you will play a critical role in shaping and delivering Borrowell’s core machine learning capabilities and influencing product direction through data-driven recommendations. You will partner closely with Product, Business, Data, and Engineering leaders to design, build, and scale ML-driven systems that personalize the member experience, power our recommendation and ranking engines, and directly impact marketplace conversion and approval outcomes.

This is a hands‑on, product‑facing role with end‑to‑end ownership — from problem framing and model design to experimentation, measurement, and iteration in production. This role is expected to operate as a technical leader, setting modeling direction and raising the bar for data science rigor across the organization.

During your first year, you can expect to:

• Own high-impact ML initiatives technical and product trade‑off decisions – Lead the design and delivery of product ranking, intent prediction, and approval likelihood models that materially improve business KPIs.
• Translate strategy into models – Work with Product and Business stakeholders to convert complex business goals into well‑defined ML problems, success metrics, and experimentation plans.
• Build, evaluate, and iterate on production models – Develop robust features, train and calibrate models, and continuously improve performance through rigorous evaluation and A/B testing.
• Drive measurable business outcomes – Connect model performance to conversion, approval rates, revenue, and member engagement, and clearly communicate impact to stakeholders.
• Establish best practices for experimentation and modeling – Raise the bar on model evaluation, calibration, drift analysis, and offline/online alignment.

• 5+ years of experience delivering data science and machine learning solutions with demonstrated ownership of high‑impact production models from problem definition through production and iteration.
• Hands‑on experience designing, building, and iterating on ranking, recommendation, or personalization models used in a production environment (e.g., offer ranking, next‑best‑action, feed ranking, eligibility routing).
• Strong proficiency in Python for data analysis, feature engineering, and modeling.
• Advanced SQL skills, including complex joins and analytical queries across large datasets.
• Deep experience with supervised learning
  , including handling class imbalance and model calibration.
• Strong background in experimentation and A/B testing
  , including metric design, offline/online evaluation and interpretation.
• Excellent communication skills — able to clearly explain complex models, trade‑offs, and impact to technical and non‑technical audiences.
• Comfortable owning ambiguous problems end‑to‑end and driving alignment across stakeholders in fast‑moving environments.

• Experience with end‑to‑end ML workflows
  , including deployment and post‑launch iteration.
• Experience working with cloud‑based data platforms (e.…