Staff Data Scientist, Rewarded Apps

Responsibilities

You will serve as the senior analytical leader for the Play business, shaping strategy through advanced modeling, experimentation, and cross-functional collaboration. You will mentor team members and translate complex data into actionable recommendations for executive leadership.

Requirements

Candidates must have 8+ years of experience in data science or quantitative strategy with advanced proficiency in Python and SQL. A strong foundation in statistics, causal inference, and machine learning is required, along with the ability to influence stakeholders without direct authority.

Skills

• Python
• SQL
• Machine learning
• Predictive modeling
• Data science
• Experimental design
• Causal inference
• Statistical analysis
• Product strategy
• Data storytelling
• Mentorship
• Feature engineering
• Marketplace dynamics
• Segmentation
• Forecasting
• A/B testing

Benefits

• Equity
• Paid time off
• Holidays

About this role

About the Role:
Fetch is looking for a Staff Data Scientist to serve as the senior analytical
and scientific leader for our Play business and broader Rewarded Apps portfolio.
Reporting to the Senior Director of User Analytics & Insights, you’ll partner
with General Managers and leaders across Product, Marketing, Engineering, and
other functions to shape how data, experimentation, and advanced analytics
inform the future of Play.

This is a strategic, hands-on individual contributor role. You’ll set the
analytical direction for Play, identify the highest-value questions for the
business, and lead complex analyses and modeling initiatives that influence
product strategy, monetization, engagement, and long-term growth. While this
role has no direct reports, you’ll mentor analysts and data scientists,
establish best practices, and raise the bar for analytical rigor across the
organization.

What You'll Do at Fetch:
* Set the analytical and scientific strategy for Play, identifying high-impact
opportunities across revenue, margin, engagement, retention, user experience,
and advertiser performance.
* Serve as a senior thought partner to business, Product, Marketing, and
Engineering leaders, proactively defining the questions analytics should
answer.
* Translate ambiguous business and product challenges into structured
analytical approaches that clearly communicate trade-offs, uncertainty, and
expected impact.
* Develop a deep understanding of the Play P&L and connect user behavior and
product performance to revenue, margin, and marketplace outcomes.
* Lead advanced analytics and data science initiatives across engagement,
retention, monetization, personalization, segmentation, and marketplace
dynamics.
* Build predictive and machine learning models that identify behavioral
patterns, forecast outcomes, prioritize opportunities, and inform product and
business strategy.
* Shape Play’s experimentation and measurement strategy, applying A/B testing,
causal inference, quasi-experimental methods, and observational analysis as
appropriate.
* Develop scalable analytical assets, feature pipelines, modeling frameworks,
and trusted measurement systems using Python and SQL.
* Partner with Product and Engineering to operationalize models, scoring
frameworks, and analytical outputs that improve the user experience and
business performance.
* Translate complex findings into clear recommendations for senior and
executive audiences, framed around customer outcomes, financial impact,
strategic risk, and opportunity cost.
* Mentor analysts and data scientists, review high-impact analyses, and
establish best practices for modeling, experimentation, documentation,
reusable code, and data storytelling.

Minimum Qualifications:
* 8+ years of experience in data science, analytics, quantitative strategy, or
a related field, including ownership of complex product or business domains.
* Advanced proficiency in Python and SQL, with experience building reusable
analytical and modeling workflows.
* Experience developing, evaluating, and operationalizing machine learning and
predictive models, including feature engineering and translating model
outputs into business decisions.
* Strong foundation in statistics, experimental design, power analysis, metric
selection, segmentation, and causal inference.
* Experience applying causal inference techniques such as
difference-in-differences, matching, synthetic controls, or related
methodologies.
* Experience developing models related to personalization, propensity,
recommendations, forecasting, retention, or lifetime value.
* Demonstrated ability to independently structure and solve ambiguous,
high-impact problems while balancing analytical rigor with business urgency.
* A track record of using analytics to drive measurable improvements in areas
such as revenue, engagement, retention, product performance, or operational
efficiency.
* Proven ability to influence senior stakeholders across Product, Engineering,
Marketing, and business teams without direct authority.
* Experience mentoring analysts or data scientists and improving the quality of
work across a broader team.
* Exceptional communication and data storytelling skills, including the ability
to explain sophisticated analytical concepts to non-technical audiences.

Preferred Qualifications:
* Experience in consumer technology, gaming, marketplaces, rewards, loyalty, or
another high-frequency digital product.
* Experience with modern analytics engineering tools and practices, including
dbt, Git/GitHub, Spark, or similar technologies.
* Experience working with businesses where user engagement, monetization,
incentives, and marketplace economics are closely connected.
* Experience combining advanced analytics with both product and commercial
strategy.

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
* Co...

About Fetch

Technology, Information and Internet · 501-1,000 employees · headquartered in Hybrid-remote workplace · founded 2013