Leads company-wide data science priorities, KPI frameworks, measurement standards, causal modeling, scenario planning, and agentic analytical automation. Builds reproducible SQL and Python workflows, validates predictive and causal relationships, establishes trusted metrics, partners with Finance, Product, Commercial, Engineering, and Data Engineering, and mentors scientists. The role drives adoption of governed self-service analytics and communicates assumptions, uncertainty, and business trade-offs to leadership.
What we’re building and why we’re building it.
Fetch helps people live rewarded every day, with a vision to become the rewards destination for everyone. We turn everyday activities into meaningful rewards, whether it’s grocery shopping, grabbing a quick meal, or playing a favorite mobile game. To date, we’ve awarded more than $1 billion in Fetch Points to our users.
Each day, more than 13 million receipts are submitted on Fetch, providing visibility into over $212 billion in gross merchandise value. This creates the largest retail-agnostic, SKU-level view of household spending, powering Fetch as an outcomes-based advertising platform that helps brands acquire and retain lifelong consumers.
The Fetch app is available on the App Store and Google Play, with more than 6 million five-star reviews from a highly engaged and loyal user base.
It’s not just our users who believe in Fetch: with investments from Softbank, ICONIQ, DST, Greycroft, and partnerships ranging from challenger brands to Fortune 500 companies, Fetch is reshaping how brands and consumers connect in the marketplace. When you work at Fetch, you play a vital role in a platform that drives brand loyalty and creates lifelong consumers with the power of Fetch points. User and partner success are at the heart of everything we do, and we extend that same commitment to our employees.
At Fetch, we value curiosity, adaptability, and the confidence to explore new tools, especially AI, to drive smarter, faster work. You don’t need to be an expert, but you should be ready to learn quickly and think critically. We welcome learners who move fast, challenge the status quo, and shape what’s next, with us. Ranked as one of America’s Best Startup Employers by Forbes for two years in a row, Fetch fosters a people-first culture rooted in trust, accountability, and innovation. We encourage our employees to challenge ideas, think bigger, and always bring the fun to Fetch.
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 help Fetch run on rigorous performance standards and scalable self-service analytics. You'll help deliver our core company KPI framework, including its underlying model, while leading reusable, company-wide analytical frameworks and automation.
The work centers on trusted metrics: standardizing how impact is measured and connecting product and business drivers to outcomes like MAU, retention, ARPU, revenue, and margin. You'll establish governed self-service and agentic workflows that reduce bespoke work and improve decision speed while maintaining scientific quality.
You'll partner with DS leadership to prioritize analytical investments, and independently lead the technical approach, delivery, and adoption of cross-team KPI, measurement, and automation workstreams.You'll shape leadership strategy, align Finance and Product on targets and trade-offs, and mentor scientists, partnering with cross-functional partners along the way.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
- Define core data science priorities across teams, deciding which questions and investments to pursue or decline
- Help deliver our core company KPI framework, including its driver tree and sensitivity modeling
- Lead reusable, company-wide analytical frameworks and automation
- Personally design, build, evaluate, and maintain agentic analytical workflows that use certified metrics to investigate KPI changes, generate evidence-backed hypotheses, and support follow-up analysis, with monitoring, failure handling, and human review where needed.
- Design reusable frameworks with evaluation and evidence traceability
- Set definitions and targets for certified metrics with owners, and resolve conflicting definitions with partners
- Build KPI trees and decompositions that connect product and business drivers to MAU, retention, ARPU, revenue, and margin
- Choose defensible models and quantify the direction, sensitivity, predictive strength, and time horizon of KPI-to-North-Star relationships
- Validate leading indicators out of sample, distinguishing arithmetic identities, predictive associations, and causal effects
- Build scenarios and defensible team targets
- Set measurement standards and defend identification assumptions, guiding decisions when randomization or causal evidence is limited
- Select observational methods when needed, using diagnostics and robustness checks
- Measure accuracy, adoption, reduced bespoke analysis, and time to decision
- Build reproducible, tested analytical workflows in SQL and Python
- Partner with Data Engineering on gold tables and data marts
- Shape leadership strategy and team accountability, aligning Finance and Product on targets, trade-offs, and when evidence warrants a change
- Partner with Product, Finance, Commercial, and Engineering to drive adoption
- Communicate assumptions and uncertainty clearly
- Mentor scientists and establish reusable KPI, measurement, and modeling standards adopted across teams
Minimum Requirements:
- 8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments
- Ability to explain which questions and investments you prioritized or declined, and how quantified KPI relationships changed planning or investment decisions
- Proven ability to define KPIs and their hierarchy with multiple stakeholders, structure complex spaces into tackle-able plans, and establish trusted metric definitions adopted across Product, Finance, Commercial, and Engineering
- Track record of aligning Finance and Product on targets, trade-offs, and when evidence warrants a change
- Experience selecting and validating statistical, predictive, and causal models for business planning, including regression, forecasting, sensitivity analysis, and uncertainty estimation
- Skilled at using models for target setting and scenario planning while distinguishing prediction from causal impact
- Demonstrated ability to set measurement standards and defend identification assumptions when randomization or causal evidence is limited, with enough experimentation knowledge to support product data scientists
- Strong skills in SQL, Python, statistics, causal inference, and forecasting
- Track record of shipping reusable dashboards, diagnostic apps, or analytical frameworks with proven accuracy, adoption, and decision impact, and partnering on productionization of robust SQL/Python assets
- History of mentoring scientists and establishing KPI, measurement, or modeling standards that raise quality across teams
- Hands-on experience automating systems with AI, including personally building and shipping agentic automation used in real analytical or business workflows, whether in production or with internal users
- Ability to explain your contribution and how the system retrieves data, uses tools, and completes tasks
- Proven approach to evaluating agentic systems for numerical and analytical accuracy, traceability, failure handling, and adoption, and reusing that approach beyond a single demo or one-off analysis
Preferred Requirements:
- Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization
- Experience owning KPI frameworks, causal measurement, or business planning across multiple teams
- Experience in centralized or platform data science
- Experience with governed self-service analytics
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.
At Fetch, we'll give you the tools to feel healthy, happy and secure through:
- Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth.
- 401(k): Fetch will match your contributions dollar for dollar, up to 4% of your eligible pay.
- Benefits for humans and pets: We offer comprehensive medical, dental, and vision plans for everyone, including your pets.
- Continuing Education: Fetch provides ten thousand per year in education reimbursement.
- Employee Resource Groups: Take part in employee-led groups that are centered around fostering a diverse and inclusive workplace through events, dialogue, and advocacy. The ERGs participate in our Inclusion Council with members of executive leadership.
- Paid Time Off: On top of our flexible PTO, Fetch observes 9 paid holidays, as well as our year-end week-long break. (Holidays will vary for Canada-based roles)
- Robust Leave Policies: 14 weeks of fully paid parental leave for all employees, plus 6 additional weeks of paid childbirth recovery leave for birthing parents, and a flexible return-to-work schedule.
- Calvin Care Cash: Employees who are welcoming new family members will also receive a one-time $2,000 incentive to assist employees with covering the cost of childcare, clothing, diapers, and much more!
- Flexible Work Environment: Collaborate with your team in one of our stunning offices, or you can work fully remotely from anywhere in the US for US-based roles. We’ll ensure you are equally equipped with the hardware and software you need to get your job done in the comfort of your home. (applicable for most roles)
Fetch is an equal opportunity employer that embraces diversity, inclusion, and respect for all individuals. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, age, national origin, marital status, veteran status, disability, or any other characteristic protected by applicable law. Our commitment to inclusivity ensures that everyone is treated with dignity and has the opportunity to succeed based on their talent, skills, and potential.
Fetch also provides reasonable accommodations to qualified individuals with disabilities or those with sincerely held religious beliefs, as required by law. If you need assistance with the application process or require an accommodation, please contact us at [email protected].
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Leads end-to-end data science and machine learning initiatives, including predictive modeling, statistical analysis, healthcare data extraction, and production deployment. Partners with business and technical leaders to develop data science roadmaps, establishes modeling and analytics standards, evaluates emerging technologies, and mentors data science professionals. The role requires strong programming, SQL, MLOps, stakeholder communication, and advanced analytics expertise.
Top Skills:
AWSAzureDatabricksGCPMlopsPythonPyTorchRRelational DatabasesScalaSparkSQLTensorFlow
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Drafts, develops, and maintains medical policies using current clinical literature and collaborates with epidemiologists, physicians, writers, and implementation experts. Leads discussions on clinical topics, analyzes evidence, presents findings, explains complex policy issues, and recommends process improvements. The role also adapts policies across health plans and supports modern content development and publication processes.
Top Skills:
Article GalaxyCptDropboxHcpcsIcd-10Icd-9Interqual GuidelinesExcelMS OfficeMicrosoft WordSharepoint
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Leads Optum Life Sciences’ epidemiology function, overseeing pharmacoepidemiology, real-world evidence, safety, post-authorization, post-market, and non-interventional research. Provides scientific oversight, client advisory leadership, quality governance, organizational management, talent development, and business-growth support. Guides teams conducting complex studies using claims, electronic health record, registry, and other real-world data. Champions responsible use of AI, analytics, and automation while maintaining scientific rigor, transparency, validation, privacy, and regulatory governance.
Top Skills:
AnalyticsArtificial IntelligenceAutomationClaims DataElectronic Health RecordsRegistry DataSAS
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
