About the role

Senior Data Scientist at Borrowell influencing product direction through data-driven recommendations. Collaborating with various teams to design and scale ML-driven systems for personalized member experiences.

Responsibilities

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.
Nice to Haves:
Experience with end-to-end ML workflows, including deployment and post-launch iteration.
Experience working with cloud-based data platforms (e.g., Snowflake, Databricks).
Familiarity with dbt, PySpark, SparkSQL, or other distributed data processing tools.
Exposure to MLOps tools (e.g., MLflow, feature stores, monitoring frameworks).
Experience working in fintech, credit, or consumer marketplaces.

The Opportunity - join and have a major impact at a growing company that is helping Canadians feel confident about money.
Comprehensive Health Benefits - medical, dental, vision, and paramedical health benefits for you and your family, with extra yearly coverage for psychotherapists and massage therapists
Additional Health Benefits - virtual benefit offering that allows you to connect 24/7 with nurses, doctors and mental health professionals
Maternity & Parental Leave Top-up - available to new parents
WFH Reimbursement - we ship you gear like a laptop, mouse, keyboard, and you can reimburse additional items to make your workplace better for you
Employee Development Benefit - annual reimbursements on payments to help your learning
Givewell Benefit - 1 paid volunteer day a year to give back to the community
Flexibility - flexible working hours and a flexible vacation policy