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Build and maintain secure, scalable registration, authentication, identity, and verification systems across FanDuel products. Develop frontend and backend software using React, TypeScript, Java, and Python; deploy cloud infrastructure on AWS; and apply testing, observability, DevOps, and software engineering best practices. Lead projects, mentor junior engineers, participate in design and code reviews, resolve complex technical issues, and improve product reliability and maintainability.

Partner with L&D leadership to design, deliver, and improve enterprise learning programs. Manage program coordination, LMS operations, vendor/stakeholder coordination, reporting, and facilitation across virtual, in-person, hybrid, and eLearning formats. Drive process improvements, learner engagement, and data-driven recommendations.

Manage qualitative and quantitative custom research (survey design, sampling, data analysis, reporting) across FanDuel verticals. Synthesize syndicated and internal data, build trackers, partner with vendors and cross-functional stakeholders, and present actionable insights to inform marketing and commercial decisions.

Product Manager responsible for advancing FanDuel’s core search and AceAI experiences. Leads multiple autonomous pods, defines problems and priorities, writes product specifications, removes blockers, and coordinates engineers, designers, analytics, and operations. Owns search relevance, query understanding, ranking, filtering, and AI-assisted betting guidance. Uses research, data analysis, competitive insights, and A/B testing to define success criteria, measure outcomes, and improve customer engagement, conversion, and retention.

Lead and manage a data science team building production-ready machine learning models to predict sports outcomes, price markets, create dashboards, and drive insights. Collaborate with product, risk, and trading teams; oversee data collection and cleaning; apply Bayesian methods; troubleshoot code; present to senior leaders; hire and develop talent; improve processes and automation.

Design, build, and maintain scalable ETL/ELT, batch and streaming data pipelines and platforms. Create reusable data models (dbt/Spark), ensure data quality and observability, collaborate with data scientists, analysts, and product teams, and mentor junior engineers while advancing data platform architecture and tooling.

Design, build, and maintain scalable batch and streaming data pipelines. Write clean code (Python, SQL, Spark), ensure data quality and reliability, monitor and troubleshoot pipelines, document sources and transformations, and collaborate with analysts, data scientists, and product teams to deliver data products and support analytics and ML use cases.

Lead and mentor a team of data engineers to design, build, and maintain scalable data pipelines, platforms, and data products. Provide technical oversight, code and architecture reviews, cross-functional partnership with product and analytics teams, and drive operational reliability, data quality, governance, and continuous improvement.

As a Machine Learning Engineer at FanDuel, you'll develop scalable ML applications, enhance user experience through intelligent systems, and collaborate across teams to validate AI insights.

The Machine Learning Engineer will design and implement search systems, develop scalable serving systems for ML, and collaborate with teams to productionize AI insights, requiring engagement with big data and machine learning frameworks.