Senior Data Scientist I, Growth & Engagement
Fetch · Canada
What we’re building and why we’re building it.
Fetch helps people live rewarded every day, with a vision to become the rewards destination for everyone. We turn everyday activities into meaningful rewards, whether it’s grocery shopping, grabbing a quick meal, or playing a favorite mobile game. To date, we’ve awarded more than $1 billion in Fetch Points to our users.
Each day, more than 13 million receipts are submitted on Fetch, providing visibility into over $212 billion in gross merchandise value. This creates the largest retail-agnostic, SKU-level view of household spending, powering Fetch as an outcomes-based advertising platform that helps brands acquire and retain lifelong consumers.
The Fetch app is available on the App Store and Google Play, with more than 6 million five-star reviews from a highly engaged and loyal user base.
It’s not just our users who believe in Fetch: with investments from Softbank, ICONIQ, DST, Greycroft, and partnerships ranging from challenger brands to Fortune 500 companies, Fetch is reshaping how brands and consumers connect in the marketplace. When you work at Fetch, you play a vital role in a platform that drives brand loyalty and creates lifelong consumers with the power of Fetch points. User and partner success are at the heart of everything we do, and we extend that same commitment to our employees.
At Fetch, we value curiosity, adaptability, and the confidence to explore new tools, especially AI, to drive smarter, faster work. You don’t need to be an expert, but you should be ready to learn quickly and think critically. We welcome learners who move fast, challenge the status quo, and shape what’s next, with us. Ranked as one of America’s Best Startup Employers by Forbes for two years in a row, Fetch fosters a people-first culture rooted in trust, accountability, and innovation. We encourage our employees to challenge ideas, think bigger, and always bring the fun to Fetch.
About the Role:
As a Senior Data Scientist focused on growth and engagement, you'll help Fetch understand user behavior and use data to shape product decisions that improve retention and engagement.You'll partner with Product, Engineering, and Design to set clear KPIs, success criteria, and guardrails that your team actually uses to make decisions. You'll independently design credible experiments and deliver clear launch, iterate, or stop recommendations.
You'll also develop predictive models that serve as the intelligence layer for our lifecycle intervention systems, from anticipating user behavior to deeper insight into product experiments. These signals help the product team tailor interventions to the right users and drive user and revenue outcomes.
Beyond whether a change worked, you'll find out who benefits and whether gains persist past novelty, and use that to shape targeting and product priorities. This is an independent, hands-on role: you'll own questions from framing to recommendation, build reusable analyses, and become a trusted voice in your product area's decisions.
What you’ll do at Fetch:
- Independently design, execute, and interpret product experiments for feature development, owning power analysis, primary metrics, and guardrails
- Frame causal questions by defining the population, outcomes, and time horizon needed to show whether a product change caused improvement
- Define KPI frameworks for teams to optimize around, linking product objectives to primary, secondary, and guardrail metrics with clear definitions and success criteria
- Recommend launch, iterate, or stop based on effect size, uncertainty, user value, and business impact
- Balance speed and rigor, and identify when more evidence could change a decision
- Turn ambiguous product questions into structured, credible analysis
- Connect metric movements to behavioral drivers and check alternative explanations
- Use product analytics to understand the user journeys and behaviors most impactful on retention and downstream outcomes, and use those insights to inform product development
- Evaluate how effects differ across user segments without overinterpreting noisy subgroup results
- Separate novelty and short-term gains from persistent, long-term value
- Develop predictive models that act as the intelligence layer for our lifecycle intervention systems
- Use audience segments and predictive signals to help the product team tailor treatment delivery to drive monthly active users and revenue, and validate that targeted treatments actually improve outcomes
- Build clear narratives that translate findings into product action, influencing priorities and launch decisions as the trusted analytical owner for your workstream
- Produce reusable analyses and share analytical knowledge across the team
- Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to conduct and scale analytical work
Minimum Qualifications:
- 5+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
- Experience owning experiment design end to end, including power analysis, primary metrics, and guardrails
- Track record of using experiment results to recommend launching, iterating, or stopping
- Ability to frame causal questions and distinguish prediction from causal impact
- Experience defining KPI frameworks for a product workstream
- Track record of influencing launch or roadmap decisions, with quantified impact on adoption, retention, engagement, revenue, or efficiency and clear personal ownership
- Experience identifying retention drivers and evaluating which users benefited and whether gains persisted
- Experience applying predictive models to segment users or forecast outcomes
- Strong proficiency in SQL and at least one programming language, preferably Python
- Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
- Ability to communicate assumptions and uncertainty clearly
- Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
Preferred Requirements:
- Product analytics experience in a consumer app or digital product, across activation, engagement, retention, or monetization
- Experience evaluating incentives, lifecycle interventions, or personalization
- Experience validating whether targeted treatments improve outcomes
- Track record of sharing reusable analyses and knowledge with your team
This is a full-time role that can be held from one of our US offices or remotely in the United States or any Canadian province (excluding Quebec), subject to appropriate work authorization. Canadian employment, if applicable, would be through Fetch’s Canadian Employer of Record.
Benefits for Canada-based employees may differ slightly to comply with applicable law(s) (e.g., paid time off, Holidays, etc.).
Fetch may use technology tools that incorporate artificial intelligence ("AI") capabilities to support certain activities within our recruiting and hiring process:
- Reviewing and organizing applications and resumes to help our recruiting team manage high volumes of submissions, including automated review of fraud signals to identify bad actors;
- Identifying candidates whose stated qualifications and experience appear relevant to an open position;
- Scheduling and coordinating interviews with candidates;
- Generating interview summaries or notes to assist recruiters and hiring managers in their review; and
- Conducting research on open roles and candidate pools to improve the effectiveness of our recruiting practices.
Fetch does not use AI tools to make hiring decisions. All decisions regarding whether to advance a candidate, extend an offer, or decline an application are made by Fetch employees, who are predominantly members of our Talent Acquisition team and relevant Hiring Managers. AI tools serve only to assist the process of recruiting talent and to in