Top Tech Jobs & Startup Jobs

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.