Who you are

- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments

- Ability to explain which questions and investments you prioritized or declined, and how quantified KPI relationships changed planning or investment decisions

- Proven ability to define KPIs and their hierarchy with multiple stakeholders, structure complex spaces into tackle-able plans, and establish trusted metric definitions adopted across Product, Finance, Commercial, and Engineering

- Track record of aligning Finance and Product on targets, trade-offs, and when evidence warrants a change

- Deep expertise building and validating ML models, including regression, causal inference, and graph models, that connect user behavior and business drivers to retention, monetization, or company outcomes

- Skilled at using models for target setting and scenario planning while distinguishing prediction from causal impact

- Demonstrated ability to set measurement standards and defend identification assumptions when randomization or causal evidence is limited, with enough experimentation knowledge to support product data scientists

- Strong skills in SQL, Python, statistics, causal inference, and forecasting

- Track record of shipping reusable dashboards, diagnostic apps, or analytical frameworks with proven accuracy, adoption, and decision impact, and partnering on productionization of robust SQL/Python assets

- History of mentoring scientists and establishing KPI, measurement, or modeling standards that raise quality across teams

- Hands-on experience automating systems with AI, including personally building and shipping agentic automation used in real analytical or business workflows, whether in production or with internal users

- Ability to explain your contribution and how the system retrieves data, uses tools, and completes tasks

- Proven approach to evaluating agentic systems for numerical and analytical accuracy, traceability, failure handling, and adoption,



and reusing that approach beyond a single demo or one-off analysis

- Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization

- Experience owning KPI frameworks, causal measurement, or business planning across multiple teams

- Experience in centralized or platform data science

- Experience with experimentation platforms

- Experience with governed self-service analytics

What the job involves

- Define core data science priorities across teams, deciding which questions and investments to pursue or decline

- Help deliver our core company KPI framework, including its driver tree and sensitivity modeling

- Lead reusable, company-wide analytical frameworks and automation

- Establish governed self-service and agentic workflows that reduce bespoke work and improve decision speed while maintaining scientific quality

- Design reusable frameworks with evaluation and evidence traceability

- Set definitions and targets for certified metrics with owners, and resolve conflicting definitions with partners

- Build KPI trees and decompositions that connect product and business drivers to MAU, retention, ARPU, revenue, and margin

- Choose defensible models and quantify the direction, sensitivity, predictive strength, and time horizon of KPI-to-North-Star relationships

- Validate leading indicators out of sample, distinguishing arithmetic identities, predictive associations, and causal effects

- Build scenarios and defensible team targets

- Set measurement standards and defend identification assumptions, guiding decisions when randomization or causal evidence is limited

- Select observational methods when needed,



using diagnostics and robustness checks

- Measure accuracy, adoption, reduced bespoke analysis, and time to decision

- Build reproducible, tested analytical workflows in SQL and Python

- Partner with Data Engineering on gold tables and data marts

- Shape leadership strategy and team accountability, aligning Finance and Product on targets, trade-offs, and when evidence warrants a change

- Partner with Product, Finance, Commercial, and Engineering to drive adoption

- Communicate assumptions and uncertainty clearly

- Mentor scientists and establish reusable KPI, measurement, and modeling standards adopted across teams

Benefits

- Equity: Hop on the rocketship and have your own stake in Fetch's success with generous equity.

- 401k Match: Fetch matches 100% of the first 4% of your 401(k) contribution.

- People Advantages: Enjoy a competitive suite of ebenfits to promote health for you and your family,. Medical, Dental, and Vision insurance.

Flexible Spending

Accounts & Health Savings Account, with automatic employer HSA contributions per pay period. Family forming benefit with $10k lifetime stipend.

- Pet Benefits: We know your furry friends are family, too. Pet insurance is fully covered for your first pet.

- Continuing Education: Fetch provides $10,000+/year in education reimbursement support for job-related courses or programs.

- Flexible Paid Time Off: At Fetch, you'll plan your time off as you see fit with our flexible PTO policy. On top of our flexible PTO, Fetch observes 9 paid holidays as well as a year-end-week-long break.

- Robust Leave Policies: Fetch offers generous leave time for health and personal needs, including 20 weeks of parental leave for primary caregivers and 14 weeks for secondary caregivers + $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers and much more!

- Flexible Work Environment: Experience our beautiful work spaces, or get things done from the comfort of your couch. Choose what's best for each day.

📌 Senior Data Scientist (Canada)
🏢 Fetch
📍 Canada