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Staff Data Scientist - Rewarded Apps
Canada - Remote
Live, first seen by us 14 days ago- Pay
- Pay not listed
- Work setting
Remote — work setting source
Listed location: Canada - Remote
Work setup in the employer’s posting: Remote
From the employer’s 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 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 posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingFetch 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.
- 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 or any Canadian province (excluding Quebec), subject to appropriate work authorization. Canadian employment, if applicable, would be through Fetch’s Canadian Employer of Record.
Read the full posting
What you’ll bring
All qualificationsCore 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.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 21, 202614 days ago
- Recorded sightings
- 28
- 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
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
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- dbt
- Spark
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.
Your next step
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Already applied? Track this application
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
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 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.).
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.
Source details
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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
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 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.).