Senior Data Scientist I, Growth & Engagement

United StatesRemotefull-timesenior

Data ScientistData

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Quick Summary

Key Responsibilities

Independently design, execute, and interpret product experiments for feature development, owning power analysis, primary metrics, and guardrails Frame causal questions by defining the population,

Requirements Summary

5+ years of experience in data science, machine learning, or applied analytics,

Technical Tools

Data ScientistData

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.

What We Offer

~1 min read

At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $159,945 - $188,171. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.

Location & Eligibility

Where is the job

United States

Remote within one country

Who can apply

About this job

Pay per year: $159,945–$188,171 a year; 9% below the $192,275 median for Data Scientist jobs on Jobera (754 salaries).
Who can apply: United States
Posted: Today
Employer: has 83 open jobs on Jobera in 2 countries.