Top Sports Data & Analytics Jobs in New York City, NY

Leads the Journey Intelligence Team’s analytical strategy and develops analysts. Builds measurement frameworks, customer segmentation, scalable data assets, and customer lifecycle analyses. Designs experiments, evaluates product and engagement initiatives, and translates complex findings into strategic recommendations. Partners with Product, Operations, and senior leadership to improve customer experiences across platforms and business verticals.

Staff Data Engineer responsible for setting technical direction, architecting scalable data platforms, leading cross-functional initiatives, improving reliability and performance, and enabling AI-assisted analytics and development. The role includes hands-on development with Python, SQL, cloud data warehouses, orchestration, infrastructure as code, Kubernetes, Kafka, and streaming pipelines, along with mentoring, technical advocacy, documentation, code reviews, and on-call troubleshooting.

Delivers custom business intelligence and analytics solutions for sports and entertainment clients. Responsibilities include understanding client needs, analyzing fan demographic, transactional, and behavioral data, monitoring data quality, building visualizations and dashboards, automating reporting, and presenting actionable insights and recommendations. The role requires collaboration with internal teams and external stakeholders and uses Tableau, SQL, Excel, and related analytics tools.

Build the financial reporting function for a new iCasino division from scratch. Own data modeling, SQL and dbt transformations, dashboards, recurring reports, KPI tracking, and business insights using Snowflake, Sigma, and Oracle. Partner with engineering, finance, compliance, operations, and commercial teams; communicate findings to stakeholders; develop scalable BI solutions; leverage GenAI tools; and mentor others on analytics and BI best practices.

Supports performance measurement, marketing insights, strategic planning, sponsorship ROI analysis, surveys, social listening, media monitoring, and client reporting for sports and entertainment brand partnerships. The role researches trends, analyzes quantitative and qualitative data, develops presentations and actionable recommendations, manages project milestones and external vendors, and guides interns. Candidates need strong analytical, problem-solving, storytelling, Excel, and PowerPoint skills, plus a bachelor's degree and 2–4 years of experience.

Leads global consumer insights and market research supporting fan development, brand health, media, marketing effectiveness, and business planning. Conducts qualitative and quantitative research, analyzes syndicated and first-party data, monitors fandom and audience trends, and translates findings into actionable recommendations and executive-ready presentations. Coordinates vendors, stakeholders, timelines, and multiple projects while supporting research process improvements and junior team development.

Analyzes affiliate ecommerce performance, translates data into actionable recommendations, develops dashboards and reporting, identifies growth opportunities, designs tests, and supports editorial, business development, and social teams. The role also maintains analytics processes, automates workflows, and leads ad hoc analysis during major commerce periods.

Leads Major League Soccer’s Marketing Science function, overseeing teams and external resources while developing marketing analytics strategy. Partners with Marketing, CRM, Technology, Product, and Data Engineering teams to improve audience targeting, personalization, campaign measurement, media investment, and fan growth. Oversees predictive modeling, AI and machine learning applications, media mix modeling, experimentation, attribution, and CRM activation. Communicates analytical insights and strategic recommendations to executive stakeholders across League and Club organizations.

Leads and scales the Growth Product Insights data practice, managing and mentoring data analysts while contributing hands-on analytical work. The role drives proactive insights, experimentation, causal inference, cohort modeling, KPI development, and strategic recommendations for product and growth leaders. It also strengthens data quality and metric governance, partners with engineering teams on complex pipelines and event data, and integrates modern analytics and generative AI tools into team workflows.

Leads customer data engineering strategy, delivery, team development, and roadmapping. Oversees data-driven product improvements, digital programs, quality initiatives, budgets, cybersecurity remediation, and portfolio management. Manages, mentors, and grows data engineering teams, including contractor teams, while guiding customer data platforms, omnichannel identity resolution, complex data modeling, and personalization-focused data science capabilities. Partners across the organization to execute strategic initiatives and build team capability.