Senior Data Scientist II, Ranking & Relevance
US - Remote
- Pay
$183,665–216,077/year · BaseAnnual period assumed — pay source
This is a full-time role that can be held from one of our US offices or remotely in the United States. Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $183,665-$216,077. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.
Read the full posting- Work setting
Remote stated — work setting source
Listed location: US - Remote
Read the full posting- Employment
Employment terms need review — employment source
Consumer product analytics experience connecting behavior to retention and monetization This is a full-time role that can be held from one of our US offices or remotely in the United States. Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $183,665-$216,077. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.
Employment type in the employer’s listing: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingYou'll own the analytical and experimentation roadmap for ranking and relevance at Fetch, partnering with Product, Engineering, and ML to improve advertiser outcomes, user value, and Fetch's long-term economics.
As the team's dedicated data scientist, you'll own the data science strategy for relevance and ranking, working closely with engineers on models that drive user engagement, rewards earned, and partner economic outcomes.
Own experiment design and turn results into launch recommendations
Partner with engineers to improve ranking models from objective through experimentation
Design measurement that handles marketplace bias and interference between advertisers
Build marketplace frameworks balancing advertiser, user and platform value
Serve as core data science partner to commercial and offer teams
From the employer’s posting
You'll own the analytical and experimentation roadmap for ranking and relevance at Fetch, partnering with Product, Engineering, and ML to improve advertiser outcomes, user value, and Fetch's long-term economics.
As the team's dedicated data scientist, you'll own the data science strategy for relevance and ranking, working closely with engineers on models that drive user engagement, rewards earned, and partner economic outcomes. You'll build frameworks that balance advertiser incrementality and delivery, user relevance and retention, and platform revenue, reward costs, and margin.
Own experiment design and turn results into clear launch recommendations
Partner closely with engineers to improve ranking models end to end, from defining what the model should optimize through experimentation
Design measurement that holds up in a marketplace, where bias and interference between advertisers can distort results
Build marketplace frameworks that balance advertiser, user, and platform value with clear success criteria and guardrails for the trade-offs
Serve as the core data science partner to commercial and offer teams, turning business goals into measurable objectives and ranking improvements
What you’ll bring
All qualificationsCore experience
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
- Experience building reusable analytical assets and mentoring other analysts or scientists
- Strong proficiency in SQL and at least one programming language, preferably Python
- Experience owning the analytical roadmap and experiments for ranking, relevance, or recommendations
- Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
- Ability to explain which questions you prioritized, which work you declined, and why
Preferred experience
- Experience in ad ranking or product search and ranking
Qualification wording
8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
Experience building reusable analytical assets and mentoring other analysts or scientists
Strong proficiency in SQL and at least one programming language, preferably Python
Experience owning the analytical roadmap and experiments for ranking, relevance, or recommendations
Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
Ability to explain which questions you prioritized, which work you declined, and why
Experience in ad ranking or product search and ranking
Tools in this posting
- Python
- SQL
- AWS
- dbt
- Snowflake
- Spark
- Airflow
Source — Tool mentions in context
- Mentor others and build reusable methods that raise the team's scientific quality and execution - Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to conduct and scale analytical work Minimum Qualifications:
- Strong modeling expertise - Strong proficiency in SQL and at least one programming language, preferably Python - Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
- Strong proficiency in SQL and at least one programming language, preferably Python - Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark Preferred Qualifications:
Posting record
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- Live
- First seen by us
- Oct 18, 2026 · 1 day ago
- Recorded sightings
- 2
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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:
You'll own the analytical and experimentation roadmap for ranking and relevance at Fetch, partnering with Product, Engineering, and ML to improve advertiser outcomes, user value, and Fetch's long-term economics.
As the team's dedicated data scientist, you'll own the data science strategy for relevance and ranking, working closely with engineers on models that drive user engagement, rewards earned, and partner economic outcomes. You'll build frameworks that balance advertiser incrementality and delivery, user relevance and retention, and platform revenue, reward costs, and margin.
You'll be the core data science partner across the go-to-market, offer development, and offer delivery teams, translating commercial goals into measurable objectives, product requirements, and ranking improvements. You'll shape senior stakeholder decisions on launch, iteration, or stopping, and mentor others while establishing reusable methods that improve the team's scientific quality and execution.
What You’ll Do at Fetch:
- Own the data science strategy and roadmap for ranking and relevance as the team's dedicated data scientist
- Partner closely with engineers to improve ranking models end to end, from defining what the model should optimize through experimentation
- Own experiment design and turn results into clear launch recommendations
- Design measurement that holds up in a marketplace, where bias and interference between advertisers can distort results
- Apply rigorous observational methods when experiments aren't possible, and defend the assumptions behind them
- Build marketplace frameworks that balance advertiser, user, and platform value with clear success criteria and guardrails for the trade-offs
- Separate true incremental gains from value that's simply shifted between advertisers, surfaces, or time periods
- Measure how changes impact different user and advertiser segments, distinguishing durable value from short-term lift
- Use findings to shape targeting and investment strategy, accounting for uncertainty
- Quantify commercial impact to guide senior leaders on priorities and product decisions
- Serve as the core data science partner to commercial and offer teams, turning business goals into measurable objectives and ranking improvements
- Communicate with technical and non-technical partners alike
- Mentor others and build reusable methods that raise the team's scientific quality and execution
- Leverage tools and technologies such as Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to conduct and scale analytical work
Minimum Qualifications:
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
- Experience owning the analytical roadmap and experiments for ranking, relevance, or recommendations
- Ability to explain which questions you prioritized, which work you declined, and why
- Cross-functional collaboration experience where product, sales, and engineering are all factors in your daily work
- Experience defining a marketplace KPI framework and resolving advertiser–user–platform trade-offs
- Track record of looking beyond a single metric's improvement to its effect on overall marketplace economics
- Experience designing measurement that accounts for selection bias, shared budgets, or spillovers
- Ability to defend experiment design and its assumptions, addressing selection bias, interference, or observational identification
- Demonstrated incremental, persistent business impact
- Track record of influencing strategy or launch decisions
- Examples of redirecting, pausing, or stopping initiatives based on quantified trade-offs
- Experience building reusable analytical assets and mentoring other analysts or scientists
- Strong modeling expertise
- Strong proficiency in SQL and at least one programming language, preferably Python
- Experience working with large-scale data systems such as Snowflake, dbt, Airflow, or Spark
Preferred Qualifications:
- Substantial experience with advertiser-funded consumer marketplaces, retail media, or ad platforms balancing advertiser, user, and platform incentives
- Experience in ad ranking or product search and ranking
- Consumer product analytics experience connecting behavior to retention and monetization
This is a full-time role that can be held from one of our US offices or remotely in the United States.
Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $183,665-$216,077. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.
Source details
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- Pay
This is a full-time role that can be held from one of our US offices or remotely in the United States. Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $183,665-$216,077. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.
- 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.
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