Senior Data Scientist I, Growth & Engagement
Canada - Remote
- Pay
- Pay not listed
- Work setting
Remote stated — work setting source
Listed location: Canada - Remote
Work setup in the employer’s listing: Remote
From the employer’s posting- Employment
Employment terms need review — employment source
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.).
Employment type in the employer’s listing: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingAs 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 partner with Product, Engineering, and Design to set clear KPIs, success criteria, and guardrails that your team actually uses to make decisions.
From the employer’s posting
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.
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.
What you’ll bring
All qualificationsCore experience
- 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
- Ability to frame causal questions and distinguish prediction from causal impact
- Experience defining KPI frameworks for a product workstream
- Experience identifying retention drivers and evaluating which users benefited and whether gains persisted
- Experience applying predictive models to segment users or forecast outcomes
Preferred experience
- Experience evaluating incentives, lifecycle interventions, or personalization
- Experience validating whether targeted treatments improve outcomes
Qualification wording
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
Ability to frame causal questions and distinguish prediction from causal impact
Experience defining KPI frameworks for a product workstream
Experience identifying retention drivers and evaluating which users benefited and whether gains persisted
Experience applying predictive models to segment users or forecast outcomes
Experience evaluating incentives, lifecycle interventions, or personalization
Experience validating whether targeted treatments improve outcomes
Education & alternatives
- Ability to communicate assumptions and uncertainty clearly - Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field. Preferred Requirements:
Tools in this posting
- Python
- SQL
- AWS
- dbt
- Snowflake
- Spark
- Airflow
Source — Tool mentions in context
- 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:
- 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
- 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
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier listing.
- Status in our records
- Live
- First seen by us
- Oct 21, 2026 · today
- Recorded sightings
- 1
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
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Job description
- 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
- 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.
- 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
- 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Canada - Remote
Working pattern and location restrictions need checking in the full posting.
- Work authorization
- 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.).
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