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: You’ll own the analytical and experimentation roadmap for ranking and relevance at Fetch, partnering with Product, Engineering, and ML to improve advertiser outcomes, user value, and Fetch’s long‑term economics.

As the team’s dedicated data scientist, you’ll own the data science strategy for relevance and ranking, working closely with engineers on models that drive user engagement, rewards earned, and partner economic outcomes. You’ll build frameworks that balance advertiser incrementality and delivery, user relevance and retention, and platform revenue, reward costs, and margin.

You’ll be the core data science partner across the go‑to‑market, offer development,



and offer delivery teams, translating commercial goals into measurable objectives, product requirements, and ranking improvements. You’ll shape senior stakeholder decisions on launch, iteration, or stopping, and mentor others while establishing reusable methods that improve the team’s scientific quality and execution.

What You’ll Do at Fetch:

Own the data science strategy and roadmap for ranking and relevance as the team’s dedicated data scientist

Partner closely with engineers to improve ranking models end to end, from defining what the model should optimize through experimentation

Own experiment design and turn results into explicit launch recommendations

Design measurement that holds up in a marketplace, where bias and interference between advertisers can distort results

Apply rigorous observational methods when experiments aren’t possible, and defend the assumptions behind them

Build marketplace frameworks that balance advertiser, user, and platform value with clear success criteria and guardrails for the trade‑offs

Separate true incremental gains from value that’s simply shifted between advertisers, surfaces, or time periods

Measure how changes impact different user and advertiser segments, distinguishing durable value from short‑term lift

Use findings to shape targeting and investment strategy, accounting for uncertainty





Quantify commercial impact to guide senior leaders on priorities and product decisions

Serve as the core data science partner to commercial and offer teams, turning business goals into measurable objectives and ranking improvements

Communicate with technical and non‑technical partners alike

Mentor others and build reusable methods that raise the team’s scientific quality and execution

Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to conduct and scale analytical work

Minimum Qualifications:

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

Experience owning the analytical roadmap and experiments for ranking, relevance, or recommendations

Ability to explain which questions you prioritized, which work you declined, and why

Cross‑functional collaboration experience where product, sales, and engineering are all factors in your daily work

Experience defining a marketplace KPI framework and resolving advertiser‑user‑platform trade‑offs

Track record of looking beyond a single metric’s improvement to its effect on overall marketplace economics

Experience designing measurement that accounts for selection bias, shared budgets, or spillovers

Ability to defend experiment design and its assumptions, addressing selection bias, interference, or observational identification

Demonstrated incremental, persistent business impact

Track record of influencing strategy or launch decisions

Examples of redirecting, pausing, or stopping initiative

📌 Senior Data Scientist II, Relevance (Winnipeg)
🏢 Fetch
📍 Winnipeg