Jobs at Fetch

Build and deliver Android features for rewards discovery, shoppable content, partner integrations, and purchase attribution. Develop within a large modular Kotlin and Jetpack Compose codebase, collaborate with product, design, backend, data, and marketing technology teams, and improve performance, reliability, engagement, and rewards redemption through testing, profiling, and scalable architecture.

Build, ship, and maintain scalable iOS features used by millions of users. Responsibilities include writing Swift code with modern iOS frameworks, designing reusable components, managing asynchronous workflows, improving performance and reliability, debugging production issues, contributing to architecture and testing strategies, participating in code reviews, and collaborating with product, design, and engineering teams through release and iteration.

Develop and release Android features for rewards discovery, shoppable content, partner integrations, and purchase attribution. Build within a large modular architecture using Kotlin, Jetpack Compose, MVVM, Hilt, Room, and modern Android tooling. Collaborate with product, design, backend, data, and marketing technology teams while improving performance, reliability, engagement, and rewards redemption across Fetch’s mobile platform.

Leads Fetch’s public relations and external communications strategy, creating technology, AI, consumer behavior, and commerce narratives. Identifies high-impact earned media and thought leadership opportunities, builds journalist relationships, manages media initiatives, and translates complex product and data developments into compelling stories. Partners with Product, Engineering, Data, Marketing, and executives to amplify launches, partnerships, cultural moments, and brand positioning.

Own the production lifecycle of ranking and recommendation models, including training, validation, deployment, monitoring, retraining, versioning, rollback, and retirement. Build scalable Spark-based feature and data pipelines, orchestration workflows, model hubs, observability, CI/CD, and reliability standards. Partner with data science and engineering teams to improve model quality, deployment speed, infrastructure efficiency, and operational resilience while mentoring teammates.

Lead engineering for Fetch’s audience products, building scalable lifecycle services, predictive and lookalike model workflows, identity matching, partner and DSP activation, monitoring, governance, and access controls. Set technical direction, make architectural decisions, guide engineers, and partner with Data Science, Product, and Data Platform to move audience models from prototypes into reliable production systems.

Build and evolve Fetch’s backend data platform, including pipelines, governed data access, delivery infrastructure, and partner integrations. Own ambiguous technical problems, lead cross-system initiatives and migrations, improve reliability and engineering efficiency, shape technical direction, collaborate across teams, and mentor engineers. The role requires strong platform engineering judgment, scalable systems experience, operational awareness, and the ability to influence stakeholders in an evolving environment.

Own product experimentation and causal analysis for growth and engagement initiatives. Define KPI frameworks, evaluate retention and user behavior, build predictive models for lifecycle interventions, and assess segmented and long-term effects. Partner with Product, Engineering, and Design to recommend launches, iterations, or stops. Translate ambiguous questions into actionable insights, influence product priorities, and create reusable analyses using Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS.

Own company-wide KPI, modeling, and measurement workstreams. Build trusted metric frameworks, KPI trees, forecasts, scenarios, causal analyses, and reproducible SQL/Python workflows connecting product drivers to retention, monetization, revenue, and margin. Partner with Data Engineering, Product, Engineering, Finance, and Commercial teams to define certified metrics, build analytical assets, drive adoption, and communicate assumptions, sensitivity, uncertainty, and actionable recommendations.

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 governed self-service analytics, and partners with Finance, Product, Commercial, Engineering, and Data Engineering. The role drives trusted metric adoption, improves decision speed, mentors scientists, and aligns leadership on targets, trade-offs, uncertainty, and investment decisions.

Leads a small data science team while remaining hands-on in building advertising audience, measurement, ranking, and data-feed models and systems. Owns technical direction, causal inference frameworks, predictive modeling, experimentation, and productionization. Mentors scientists, partners with product, engineering, sales, and business development, communicates methodology to customers and executives, and establishes scalable standards for measuring advertising impact.

Lead data science strategy for Fetch’s Play and Rewarded Apps business. The role develops predictive and machine learning models, designs experiments and causal analyses, builds scalable analytical workflows, and connects user behavior to revenue, engagement, retention, and marketplace outcomes. This senior individual contributor partners with Product, Marketing, Engineering, and executives, operationalizes analytical solutions, communicates recommendations, mentors data scientists, and establishes best practices for rigorous modeling, experimentation, documentation, and data storytelling.

Own product experimentation, causal analysis, KPI frameworks, predictive modeling, and user segmentation to improve growth, engagement, retention, and revenue. Partner with Product, Engineering, and Design to translate ambiguous questions into rigorous analyses and launch recommendations. Develop lifecycle intervention intelligence, evaluate treatment effects and persistence, communicate uncertainty, and influence roadmap decisions through reusable analyses and clear narratives.

Own company-wide KPI, modeling, and measurement workstreams; develop trusted metrics, KPI trees, forecasts, causal analyses, scenarios, and diagnostic tools. Partner with Data Engineering, Product, Engineering, Finance, and Commercial teams to connect business drivers to retention, monetization, revenue, and margin. Build reproducible SQL and Python workflows, communicate uncertainty and assumptions, and drive adoption of analytical frameworks and recommendations.

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.

Own the complete machine learning model lifecycle, from experimentation and validation through deployment, monitoring, retraining, rollback, and retirement. Build reusable training, evaluation, deployment, orchestration, and CI/CD infrastructure. Establish model promotion standards, versioning, lineage, monitoring, alerting, and incident-response processes. Partner with data scientists to preserve scientific validity, improve reliability and efficiency, support delayed-label use cases, mentor teammates, and define MLOps priorities.

Principal software engineering leader responsible for architecting, building, and operating Fetch’s data products, including audience creation, measurement pipelines, partner integrations, APIs, and production workflows. The role combines hands-on development, system design, data quality and reliability ownership, technical strategy, cross-functional collaboration, and mentorship. Candidates should have extensive experience delivering data-intensive products, advertising or measurement platforms, scalable production software, and machine learning systems in partnership with data science teams.

Own end-to-end brand campaign execution, including campaign configuration, partner assets, product catalogs, point attribution, and redemption logic. Coordinate timelines across teams, support Account Managers, translate promotion requirements into operational inputs, track risks and milestones, and improve processes through automation and AI tools. Serve as a subject-matter expert while contributing to initiatives that improve partner and user experiences.

Lead the technical direction and multi-quarter roadmap for Fetch’s CI/CD and software delivery infrastructure. Design scalable pipelines, deployment systems, quality gates, developer automation, and observability. Improve build and test performance, release reliability, developer feedback, and engineering velocity across backend, frontend, mobile, infrastructure, and security teams. Drive adoption, mentor senior engineers, evaluate technologies, and explore AI-assisted development and operational workflows.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.