Senior Data Scientist I, Monetization

Responsibilities

You will independently own a defined audience or measurement product, managing the full lifecycle from problem framing to delivery. You will partner with cross-functional teams to translate advertiser goals into predictive models and actionable datasets.

Requirements

The role requires 5+ years of experience in data science or machine learning with a track record of owning complex analytical products. Candidates must possess strong skills in SQL, Python, applied statistics, and causal inference.

Skills

• Data science
• Machine learning
• Applied analytics
• SQL
• Python
• Statistical modeling
• Causal inference
• Predictive modeling
• Data validation
• Product management
• Audience modeling
• Measurement
• Data engineering
• Experimentation
• Population inference

Benefits

• Equity
• Paid time off
• Holidays

About this role

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 I, you’ll independently own a defined audience or
measurement product, from framing the problem to delivering it. Most of your
work will support our third-party data products business, and you’ll also apply
what you learn to first-party user monetization. You’ll own the full loop:
building informed audiences, extending them beyond Fetch’s user base, measuring
off-platform outcomes through receipts, and using those results to make the next
audience better.

This is a hands-on scientific and product role. You’ll partner closely with
Product, Engineering, Sales, and GTM, and you’ll be in the room with customers
explaining what the product does, why it works, and where its limits are.

What you’ll do at Fetch

* Independently own a defined audience or measurement product, from problem
framing through delivery
* Translate advertiser goals and purchase behavior into audience definitions,
labels, and predictive models
* Build and validate statistical expansion beyond Fetch users, testing quality,
calibration, and reach on held-out populations while keeping observed
purchases distinct from inferred propensity
* Combine receipt, partner, panel, survey, and contextual data into reliable
datasets, accounting for linkage uncertainty, missingness, and coverage, and
applying weighting or calibration where warranted
* Design credible studies linking ad exposure to receipt-observed purchases,
using experiments when feasible and well-justified observational methods when
they aren’t
* Check receipt coverage, exposure matching, selection bias, and uncertainty,
and keep attribution and incrementality distinct
* Turn customer problems into scoped products with clear success criteria and
launch recommendations, balancing audience quality, reach, advertiser value,
user value, revenue, and cost
* Feed campaign outcomes back into audiences and models, using holdouts and
fresh data to confirm improvements are real
* Partner with Sales and GTM to shape pilots and explain the product’s value,
presenting methods and limitations without overpromising precision or lift
* Build reproducible datasets, analyses, and validation checks, partnering with
Product, Engineering, and ML engineers to move prototypes into production
* Document your methods, share reusable code, and pass on what you learn to the
team

In your Toolbox

* 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 an audience, measurement, or data product from an ambiguous
question through delivery and a business decision
* A track record of working regularly with product, engineering, and commercial
partners, with the ability to clearly explain both the customer need and your
own contribution
* Experience building useful datasets from fragmented, incomplete, or biased
sources, and showing how you assessed their validity
* Strong population inference skills, including generalizing from an observed
sample to a broader population and checking who’s missing
* Experience building propensity or audience models and validating them against
real-world usefulness (population coverage, calibration, and measured
outcomes), not just offline accuracy, then using the results to improve the
next iteration
* Hands-on causal inference experience, including designing an experiment or
observational study you can defend (the comparison, assumptions, diagnostics,
and limits) and separating attribution from true incrementality
* Strong SQL, Python, applied statistics, and predictive modeling skills, plus
a habit of building reusable, reproducible assets
* The ability to explain scientific findings clearly to nontechnical and
customer audiences
* Sound judgment about when to move independently and when to seek review
because assumptions or scope have outrun the evidence

Nice to haves

* Applied experience in monetization data science, audience development,
advertising measurement, market research, or consumer panels, especially
where you tied data work to customer or commercial value is strongly
preferred
* Experience working with panel, survey, consumer research, or purchase data
* A background in political science, survey methodology, econometrics,
demography, or another quantitative field where you built strong datasets
with limited resources and made explicit inferences about populations from
sparse data

This is a full-tim...

About Fetch

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