Genius Sports

London
Total Offices: 2
1,800 Total Employees
Year Founded: 2001

Teams at Genius Sports

Recently posted jobs

10 Days AgoSaved
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Hybrid
London, Greater London, England, GBR
Easy Apply
AdTech • Artificial Intelligence • Machine Learning • Marketing Tech • Software • Sports • Big Data Analytics
Leads Legend’s 25+ person, multi-location finance function across reporting, payables, receivables, treasury, and payroll. The role oversees finance operating-model transformation, process redesign, automation, controls, systems improvement, post-acquisition integration, and organizational scaling. It requires strong stakeholder management, technical finance expertise, and the ability to balance strategic transformation with hands-on operational leadership across multiple jurisdictions.
11 Days AgoSaved
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Hybrid
London, Greater London, England, GBR
Easy Apply
AdTech • Artificial Intelligence • Machine Learning • Marketing Tech • Software • Sports • Big Data Analytics
Own portfolio-wide technical SEO strategy and performance across major gaming and sports domains. Lead investigations into crawling, rendering, indexation, architecture, international SEO, migrations, structured data, JavaScript SEO, and web performance. Partner with Product and Engineering to prioritize and deliver measurable impact. Build automated monitoring, diagnostics, AI-enabled workflows, tools, guardrails, and reusable frameworks while influencing senior stakeholders and coaching SEO teams.
17 Days AgoSaved
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Hybrid
London, Greater London, England, GBR
Easy Apply
AdTech • Artificial Intelligence • Machine Learning • Marketing Tech • Software • Sports • Big Data Analytics
Design, build, test, maintain, and debug reliable software features and systems. Collaborate with product managers, designers, and engineers to translate requirements into technical solutions. Participate in technical design discussions, code reviews, testing, and performance improvements while following established architecture and development standards. Work independently on defined tasks, communicate progress and trade-offs, and use AI-assisted tools responsibly to improve coding, debugging, documentation, and testing workflows.