Fetch

Staff Data Scientist, Rewarded Apps

US - Remote

Live, first seen by us 56 days ago

Pay: Pay not listedSimilar roles state $118K–$193K
Work setting: Remote — work setting source
Listed location: US - Remote
Read the full posting
Employment: Employment terms need review — employment source
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. This is a full-time role that can be held from one of our US offices or remotely in the United States. Role Responsibilities:
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting

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.

This is a strategic, hands-on individual contributor role.

Set analytical and scientific strategy for Play across revenue, engagement and retention
Build predictive and machine learning models to forecast outcomes and prioritize opportunities
Shape experimentation and measurement strategy using A/B tests and causal inference
Build scalable analytical assets and modeling frameworks in Python and SQL
Present findings and recommendations to senior and executive audiences

From the employer’s posting

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.

Set the analytical and scientific strategy for Play, identifying high-impact opportunities across revenue, margin, engagement, retention, user experience, and advertiser performance.

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.

Translate complex findings into clear recommendations for senior and executive audiences

People management: No direct reports stated — people management source
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. This is a full-time role that can be held from one of our US offices or remotely in the United States.
Read the full posting

What you’ll bring

All qualifications

Core experience

8+ years of experience in data science, analytics, quantitative strategy, or a related field, including ownership of complex product or business domains.
Experience developing, evaluating, and operationalizing machine learning and predictive models, including feature engineering and translating model outputs into business decisions.
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.
Proven ability to influence senior stakeholders across Product, Engineering, Marketing, and business teams without direct authority.

Preferred experience

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.

Qualification wording

8+ years of experience in data science, analytics, quantitative strategy, or a related field, including ownership of complex product or business domains.

Experience developing, evaluating, and operationalizing machine learning and predictive models, including feature engineering and translating model outputs into business decisions.

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.

Proven ability to influence senior stakeholders across Product, Engineering, Marketing, and business teams without direct authority.

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.

Apply at Fetch

Posting record

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Status in our records: Live
First seen by us: Sep 9, 202656 days ago
Recorded sightings: 97
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 56

Up longer than most. Similar jobs usually come down between day 7 and day 55.

From 9,988 similar postings that came down. Coming down is not always a hire.

Fetch is hiring

29 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Data Scientist hiring is picking up
Takes jobs down at a usual pace

Hiring record

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Where the posting names them

- 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.

- 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.

- 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.

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About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025: $120,230
Expected change, 2025 to 2035: 34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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:

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.

This is a full-time role that can be held from one of our US offices or remotely in the United States.

Role Responsibilities:

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 Requirements:

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 Requirements:

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.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.

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