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Leads backend engineering for a high-scale sports product, designing APIs, services, microservices, data pipelines, and scalable cloud deployments. Responsibilities include architecture, performance and security optimization, real-time data processing, code reviews, testing, production releases, technical specifications, mentoring, task delegation, blocker resolution, hiring, and developer onboarding.

Build and deploy production ML systems and end-to-end pipelines, translate business problems into mathematical frameworks, conduct experimentation (A/B, causal inference, uplift), maintain real-time models, and mentor junior team members.

Lead end-to-end product lifecycle for mobile and web sports products, collaborating with design, development, BI, and content teams. Define and track data-driven KPIs, write clear specs and wireframes, conduct market research, and use generative AI tools to accelerate product definition and delivery. Drive execution, post-launch optimization, and rapid iteration in a fast-paced environment.

Serve as the Monetization data authority: analyze large-scale datasets, define and monitor KPIs/OKRs, build dashboards, perform statistical and behavioral analyses, support AI-driven BI architecture, and provide actionable product and monetization recommendations.

Manage and optimize paid user acquisition, re-engagement, and retention campaigns across Meta, Google, Apple Search Ads, DSPs and ad networks. Run experiments and A/B tests, analyze attribution and cohort data, scale growth initiatives, collaborate with product/creative/data teams, and report performance to improve installs, retention, engagement, and revenue.

Own end-to-end tracking and signal-delivery for global performance marketing: detect and resolve tag/CAPI/reverse-ETL incidents, audit event/conversion data across major ad platforms, validate events in Snowflake using SQL, manage AppsFlyer and GTM configs, and document technical incidents for stakeholders.