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.
Senior Data Scientist II, Monetization
US - Remote
Live, first seen by us 19 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 hands-on product leadership role. You’ll act as owner and seller for your domain alongside Product, Engineering, Sales, and GTM, shaping what gets built, how it’s positioned, and what claims the evidence can support. 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 postingFetch is built on real purchase data, shared by millions of users scanning their receipts.
As a Senior Data Scientist II, you’ll own the scientific and product roadmap for a Monetization domain, connecting first-party user monetization with our third-party data products.
Own the scientific and product roadmap for the Monetization domain
Set standards for building and expanding audiences beyond Fetch users
Own measurement methodology linking ad exposure to receipt-observed purchases
Turn bespoke studies into repeatable products
Lead the scientific case with Sales and GTM, from pilots to positioning
From the employer’s posting
Fetch is built on real purchase data, shared by millions of users scanning their receipts. In Monetization, we turn that signal into products advertisers rely on: audiences built from actual shopping behavior, and measurement that shows whether a campaign changed what people bought.
As a Senior Data Scientist II, you’ll own the scientific and product roadmap for a Monetization domain, connecting first-party user monetization with our third-party data products. You’ll lead the full flywheel: informed audience creation, statistical expansion beyond Fetch’s user base, receipt-based off-platform measurement, and continuous audience improvement.
Own the scientific and product roadmap for your domain
Set the standards for how audiences are created, evaluated, and expanded beyond Fetch users
Own measurement methodology for complex studies linking ad exposure to receipt-observed purchases
Turn bespoke studies into repeatable products
Lead the scientific case with Sales and GTM, from customer discovery and pilots to positioning and handling buyer objections
What you’ll bring
All qualificationsCore experience
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated leadership of complex analytical products in product-driven environments
- Experience defining a scientific or data-product roadmap, and the ability to explain what you prioritized, what you declined, and why
- Experience leading cross-functional delivery with Sales, GTM, Product, and Engineering, including shaping customer pilots and defending product value directly
- Experience with audience expansion, panel calibration, data fusion, or measurement products that held up beyond the original sample
- Ownership of complex causal measurement, including defending your assumptions under scrutiny and changing a recommendation when the evidence fell short
- Experience mentoring scientists and establishing reusable methods that improved quality beyond your own work
Preferred experience
- Experience translating market research or quantitative social science into repeatable products and customer or commercial decisions
Qualification wording
8+ years of experience in data science, machine learning, or applied analytics, with demonstrated leadership of complex analytical products in product-driven environments
Experience defining a scientific or data-product roadmap, and the ability to explain what you prioritized, what you declined, and why
Experience leading cross-functional delivery with Sales, GTM, Product, and Engineering, including shaping customer pilots and defending product value directly
Experience with audience expansion, panel calibration, data fusion, or measurement products that held up beyond the original sample
Ownership of complex causal measurement, including defending your assumptions under scrutiny and changing a recommendation when the evidence fell short
Experience mentoring scientists and establishing reusable methods that improved quality beyond your own work
Experience translating market research or quantitative social science into repeatable products and customer or commercial decisions
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 15, 202619 days ago
- Recorded sightings
- 34
- 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
Time since we first saw it
Day 19
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
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
Where the posting names them
- Influence senior stakeholders and commercial commitments with clear, evidence-backed recommendations - Stay hands-on in SQL, Python, statistical modeling, and causal inference - Mentor scientists and establish methods that raise quality across the domain
- Evidence of influencing senior stakeholders, such as times when evidence changed a pitch, commitment, or investment - Hands-on depth in SQL, Python, statistical modeling, and causal inference - Experience mentoring scientists and establishing reusable methods that improved quality beyond your own work
Your next step
Complete your application on jobs.gem.com. The employer’s form will show what is required.
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 built on real purchase data, shared by millions of users scanning their receipts. In Monetization, we turn that signal into products advertisers rely on: audiences built from actual shopping behavior, and measurement that shows whether a campaign changed what people bought.
As a Senior Data Scientist II, you’ll own the scientific and product roadmap for a Monetization domain, connecting first-party user monetization with our third-party data products. You’ll lead the full flywheel: informed audience creation, statistical expansion beyond Fetch’s user base, receipt-based off-platform measurement, and continuous audience improvement.
This is a hands-on product leadership role. You’ll act as owner and seller for your domain alongside Product, Engineering, Sales, and GTM, shaping what gets built, how it’s positioned, and what claims the evidence can support.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
Role Responsibilities:
- Own the scientific and product roadmap for your domain, deciding what to build, what to sequence, and what to decline
- Set the standards for how audiences are created, evaluated, and expanded beyond Fetch users
- Make the call on reach–precision and revenue–cost trade-offs, favoring scalable products over one-off customization
- Shape how we combine receipt, partner, panel, and survey data, and decide which data investments are worth making
- Own measurement methodology for complex studies linking ad exposure to receipt-observed purchases
- Define what results can and can’t support, especially when a causal claim or generalization goes beyond the evidence
- Turn bespoke studies into repeatable products
- Build the feedback loop between audiences and measurement, with the holdouts and monitoring to trust what it tells you
- Connect first-party monetization with third-party products, including using audience insights to acquire and engage high-value users
- Lead the scientific case with Sales and GTM, from customer discovery and pilots to positioning and handling buyer objections
- Influence senior stakeholders and commercial commitments with clear, evidence-backed recommendations
- Stay hands-on in SQL, Python, statistical modeling, and causal inference
- Mentor scientists and establish methods that raise quality across the domain
Minimum Requirements:
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated leadership of complex analytical products in product-driven environments
- Experience defining a scientific or data-product roadmap, and the ability to explain what you prioritized, what you declined, and why
- Experience leading cross-functional delivery with Sales, GTM, Product, and Engineering, including shaping customer pilots and defending product value directly
- A track record of building differentiated datasets or audience products from imperfect sources, with clear trade-offs on coverage, validity, and cost
- Experience with audience expansion, panel calibration, data fusion, or measurement products that held up beyond the original sample
- Ownership of complex causal measurement, including defending your assumptions under scrutiny and changing a recommendation when the evidence fell short
- Judgment on reach–precision and revenue–cost trade-offs, including recognizing when more scale reduced value
- Sustained audience or monetization gains and customer adoption, with measured outcomes used to redirect product strategy
- Evidence of influencing senior stakeholders, such as times when evidence changed a pitch, commitment, or investment
- Hands-on depth in SQL, Python, statistical modeling, and causal inference
- Experience mentoring scientists and establishing reusable methods that improved quality beyond your own work
Preferred Requirements:
- Substantial ownership of audience, measurement, or monetization data products in advertising, retail media, market research, consumer panels, or a comparable commercial setting is strongly preferred
- Experience translating market research or quantitative social science into repeatable products and customer or commercial decisions
- A background in political science, survey methodology, econometrics, demography, or another resource-constrained quantitative field
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
US - Remote
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.