Meet Fetch AI & Data AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact.

Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use.

Practitioners across this org contribute hands‑on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows.

About the role: Fetch is at a critical inflection point in how data and science inform the company's most key decisions. With millions of monthly active users, rich item‑level purchase data, and increasing investment in AI‑driven products like FetchGPT, Fetch has an opportunity to establish a rigorous, scalable measurement and causal reasoning foundation that powers pricing, incentives, growth, marketing investment, and financial planning.

We are seeking a Staff Data Scientist to serve as the company‑wide scientific and measurement leader. This role goes beyond traditional analytics or domain ownership. You will define how Fetch measures value, reasons about causality,



and translates evidence into executive decisions. You will own core measurement frameworks, architect semantic and metric foundations, and set the scientific quality bar across analytics, experimentation, and strategic modeling.

Within your first year, you will define Fetch's MAU × ARPU measurement operating system, establish canonical metrics and semantic standards powering FetchGPT and executive reporting, and deliver strategic models such as marketing mix, elasticity, and incentive sensitivity that directly inform leadership decisions.

What You'll Do at Fetch: Company Measurement and Causal Strategy

Define and own Fetch's company-level measurement framework anchored in MAU × ARPU.

Establish decision frameworks for pricing, incentives, and value trade-offs.

Set standards for evidence quality, uncertainty, and confidence in decision‑making.

Define the causal reasoning model used across product, growth, marketing, and finance.

Own the scientific capability roadmap including elasticity, value curves, MMM, and forecasting.

Semantic and Data Architecture

Architect the semantic mart and metric logic powering FetchGPT and scalable insights.

Define canonical metric definitions and unify logic across experimentation platforms, dashboards, and diagnostics.





Partner with Analytics Engineering and Data Platform to build foundational data assets.

Establish BI standards and eliminate redundant or conflicting dashboards.

Scientific Governance and Experimentation

Serve as the quality bar for high‑impact analytics and diagnostics.

Review strategic analyses to ensure correct interpretation and mechanism alignment.

Set scientific rules for experimentation and validate high‑risk tests such as pricing and incentives.Ensure observational and experimental results reconcile cleanly.

Create templates and interpretation guides to standardize rigor.

Strategic Modeling Ownership

Own cross‑company models that drive executive decisions, including marketing mix modeling, elasticity and incentive sensitivity, value expectation curves, strategic forecasting, and financial mechanism models supporting MAU × ARPU planning.

Org‑Wide Scientific Leadership

Raise the scientific maturity of the data science and analytics organization.

Design upskilling programs in statistics, causality, modeling, and storytelling.

Author best‑practice modeling libraries and documentation.

Serve as a technical anchor and thought partner for senior ICs across the org.

Establish norms for rigorous, transparent, mechanism‑driven insights.

Technical Excellence

Apply advanced statistical and causal methods to company‑level problems.

Build scalable, production‑ready analytical frameworks in partnership with engineering.

Champion best practices in experimentation design, model validation, and reproducibility.

Leverage modern analytics tooling such as Python, SQL, Snowflake, dbt, and experimentation platforms.

Minimum Qualifications

8+

📌 Staff Data Scientist, Ad Platform (Winnipeg)
🏢 Fetch
📍 Winnipeg