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Fetch
is hiring
Data Analyst, User Analytics
About Our Company
Fetch helps people live rewarded, with a vision to create the rewards destination for everyone. Through Fetch Points, the platform transforms everyday actions into rewarding moments, with more than $1 billion in Fetch Points awarded to date.
Every day, more than 13 million receipts are submitted on Fetch, creating visibility into $212 billion in gross merchandise value and delivering the largest retail-agnostic, SKU-level view of household spending. This unmatched dataset powers Fetch as an outcomes-based advertising platform that acquires and retains lifelong consumers.
The Fetch app is available for download on the App Store and Google Play and has earned more than 6 million five-star reviews.
Job Description & Responsibilities
About the Role:
As a Data Analyst on the User Analytics & Insights team, you will help cross-functional teams make better decisions through data. This role will support one of two business areas: Marketing or Apps. In either area, you will partner with Product, Marketing, Growth, Engineering, Data, and Business teams to understand user behavior, measure performance, support experimentation, and create reporting that helps teams track progress against key goals.
This role is ideal for someone who is highly analytical, comfortable working with large datasets, and able to turn business questions into clear analysis, dashboards, and recommendations. You will be responsible for building and maintaining self-service reporting, creating user segments, supporting experiment setup and analysis, and helping stakeholders understand what is happening, why it is happening, and what actions to take next.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
Role Responsibilities:
Data Analysis & Business Partnership:
Partner with Product, Marketing, Growth, Engineering, and Business stakeholders to answer key questions about user behavior, performance, engagement, conversion, and retention.
Translate business questions into structured analytical plans using SQL, visualization tools, and statistical thinking.
Conduct routine and ad hoc analyses to identify trends, diagnose metric movements, and surface opportunities for improvement.
Clearly communicate findings, implications, and recommended next steps to technical and non-technical stakeholders.
Support decision-making by connecting data insights to user experience, business outcomes, and team priorities.
Document assumptions, definitions, methodologies, and key findings so analysis is reusable and easy to understand.
Dashboarding & Reporting:
Build, maintain, and improve dashboards that track key business, product, marketing, app, and user behavior metrics.
Create scalable self-service reporting that allows stakeholders to monitor performance and reduce one-off data requests.
Ensure dashboards are accurate, clearly documented, and easy for cross-functional partners to use.
Monitor core KPIs and investigate changes in trends, performance, or data quality.
Partner with Analytics Engineering and Data Engineering to improve data definitions, reporting logic, and source-of-truth data assets.
Experimentation & Measurement:
Support experiment setup and design, including hypothesis development, metric selection, audience definition, and test-readiness checks.
Conduct MDE calculations, power analysis, and sample size estimates to help teams understand experiment feasibility.
Analyze A/B test results, including topline impact, segment-level performance, statistical significance, and follow-up questions.
Partner with Product, Marketing, and Data Science teams to ensure experiments are measured consistently and interpreted accurately.
Communicate experiment results clearly to help teams decide whether to launch, iterate, or stop an initiative.
User Segmentation:
Create and maintain user segments to support analysis, experimentation, lifecycle programs, product experiences, and business reporting.
Analyze user cohorts based on behavioral, lifecycle, engagement, acquisition, or product usage signals.
Help stakeholders understand how different user groups behave and where opportunities exist to improve engagement, conversion, retention, or monetization.
Support audience sizing, segment performance tracking, and readouts for key initiatives.
For marketing-focused work, support campaign and lifecycle audience creation.
For apps-focused work, support segmentation related to app usage, feature adoption, engagement, and product funnels.
Requirements
Minimum Qualifications:
2+ years of experience in analytics, data analysis, product analytics, marketing analytics, business analytics, or a related field.
Strong proficiency in SQL for data manipulation, analysis, validation, and reporting.
Experience building dashboards and visualizations in tools such as Hex, Tableau, Looker, Grafana, Mode, or similar platforms.
Working knowledge of A/B testing concepts, including hypothesis creation, metric selection, sample sizing, segmentation, and result interpretation.
Experience creating user segments, cohorts, or audience groups for analysis, experimentation, reporting, or targeting.
Ability to analyze funnels, retention, engagement, conversion, campaign performance, app behavior, or other user/business metrics.
Strong attention to detail and ability to identify data quality issues.
Strong communication skills, with the ability to explain findings clearly to both technical and non-technical audiences.
Ability to manage routine analytical requests independently while escalating ambiguity, blockers, or trade-offs with clear context.
Comfort working in a fast-paced environment with evolving priorities and imperfect data.
Preferred Qualifications:
Experience with dbt or analytics engineering workflows.
Experience using Git/GitHub for version control, collaboration, or code review.
Experience with Python for data analysis, automation, visualization, or statistical analysis.
Familiarity with martech, lifecycle marketing, campaign platforms, CDPs, attribution, or audience activation tools.
Familiarity with app analytics, event-based tracking, product instrumentation, feature adoption analysis, or app engagement metrics.
Experience partnering with Product, Marketing, Growth, or Engineering teams.
Comfort using Google Sheets for collaboration and lightweight analysis.
What we offer
Equity: We offer full-time employees equity in Fetch, so that everyone can benefit from Fetch’s growth.
401k Match: Dollar-for-dollar match up to 4%.
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.
Robust Leave Policies: 20 weeks of paid parental leave for primary caregivers, 14 weeks for secondary caregivers, 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. 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)
