Manager, Data Science
Confirmed on the employer's own hiring board on Nov 6, 2026. First seen by Alion on Nov 5, 2026. Questrade scores A on the Alion truth index.
What’s in it for you as an employee of QFG?
Health & wellbeing resources and programs
Paid vacation, personal, and sick days for work-life balance
Competitive compensation and benefits packages
Work-life balance in a hybrid environment with at least 3 days in office
Career growth and development opportunities
Opportunities to contribute to community causes
Work with diverse team members in an inclusive and collaborative environment
This job posting is for an existing vacancy.
We’re looking for our next Manager, Data Science. Could It Be You?
This role will be responsible for:
The Manager, Data Science leads the vision and technical execution of data science and marketing science across Marketing and Product at Questrade. Operating as a hands-on technical leader, this role spearheads our unified marketing measurement strategy—combining media mix modeling (MMM), incrementality testing, and attribution to determine the commercial impact of brand and performance investments. The Manager designs predictive growth models (such as client lifetime value, propensity, and retention) that directly inform daily business operations, establishes production-grade model standards, and mentors a high-performing data science team while actively writing and reviewing code.
Need more details? Keep reading…
In this role, responsibilities include but are not limited to:
Data Science Vision & Strategic Roadmap: Define and drive the data science and marketing science vision for Marketing and Product, establishing high technical standards and translating business growth priorities into a scalable modeling roadmap.
Comprehensive Marketing Measurement Strategy: Own the end-to-end marketing measurement framework, unifying media mix modeling (MMM), incrementality/geo testing, and multi-touch attribution into a cohesive view to guide capital allocation across brand and performance channels.
Client Growth & Predictive Lifecycle Modeling: Architect, build, and deploy high-impact predictive models—including client lifetime value (LTV), cross-sell/upsell propensity, and churn/retention—directly embedding them into day-to-day product and marketing operations.
Rigorous Model Governance & Production Standards: Hold all data science products to strict production criteria: ensuring business value is sized upfront, models are systematically validated against holdouts or baseline controls, and pipelines run reliably in production environments.
Hands-On Engineering & AI Workflow Adoption: Maintain an active hands-on engineering presence by writing, debugging, and reviewing production Python, SQL, and dbt models (on BigQuery, Databricks, or Snowflake), while utilizing AI coding agents to accelerate delivery with rigorous validation.
External Agency & Measurement Vendor Governance: Direct and govern external measurement partners, data vendors, and agency relationships—critically evaluating and pressure-testing their statistical methods, assumptions, and deliverables to ensure integrity.
Team Leadership & Statistical Authority: Lead, mentor, and develop a high-performing team of data scientists; act as the organization's subject matter expert on causal inference, experimentation design, and statistical rigor for adjacent analysts and cross-functional partners.
Comfortable using AI tools in day-to-day modeling and coding work, with the judgment to validate their output.
So are YOU our next Manager, Data Science? You are if you have…
Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Quantitative Marketing, or equivalent practical experience.
7+ years of progressive experience in data science, marketing science, or advanced analytics, with a proven track record of models directly influencing marketing investments or product growth.
Deep practical expertise in media mix modeling (MMM), incrementality testing, geo-testing, multi-touch attribution, causal inference, and client lifetime value (LTV) / propensity modeling.
Advanced proficiency in Python for building production machine learning and statistical models; strong SQL and dbt expertise on cloud data warehouses (BigQuery, Databricks, or Snowflake).
Demonstrated experience directing external measurement agencies, vendors, or consulting partners, with the ability to critically pressure-test statistical methodologies.
Proven track record of leading, mentoring, and developing data scientists while remaining actively hands-on with modeling and code.
Additional kudos if you…
Master’s or Ph.D. in a quantitative discipline (e.g., Statistics, Econometrics, Machine Learning, Applied Mathematics).
Regular hands-on experience utilizing modern AI coding agents (such as Claude Code) to accelerate model development, coupled with rigorous validation of AI outputs.
Experience building a marketing science or data science practice from scratch in a fast-paced or greenfield environment.
Prior experience in fintech, digital banking, online brokerage, or regulated customer data environments.
Compensation Information:
Base salary range: $140,000 - $180,000
The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles.
Sounds like you? Click below to apply!
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