Senior Data Strategist for Sports Tech & AI Architecture
CapTech
Reston (VA)
On-site
USD 120,000 - 150,000
Full time
14 days+
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Benefits offered by this job
Certification and tuition support
Mental health well-being platform
Fertility and family-forming coverage
Stipend for lifestyle benefits
Employee-led committees fostering inclusion
Opportunities for community engagement
401(k) Matching with no vesting period
Job summary
A leading consulting firm is seeking a visionary Lead Data Strategist to drive data transformation in the sports industry. This role blends strategic consulting with technical leadership, requiring expertise in data strategy, cloud architecture, and advanced analytics. Key responsibilities include defining enterprise-level data strategies, architecting cloud solutions, and developing predictive analytics models to enhance athlete performance and fan engagement. The ideal candidate will have extensive experience in data architecture and a strong understanding of the sports industry's dynamics.
Qualifications
Extensive experience in data strategy and architecture leadership.
Expertise in cloud technologies including AWS, Azure, and GCP.
Strong comprehension of the sports industry and digital transformation.
Responsibilities
Define and execute enterprise-level data strategies.
Architect cloud-based solutions for real-time data ingestion.
Develop computer-vision models for player tracking.
Establish frameworks for data sharing across ecosystems.
Drive predictive analytics for fan engagement.
Skills
Data strategy
Cloud architecture
Sports innovation
AI/ML
Real-time analytics
Tools
Python
SQL
Databricks
Snowflake
AWS
Azure
GCP
Job description
A leading consulting firm is seeking a visionary Lead Data Strategist to drive data transformation in the sports industry. This role blends strategic consulting with technical leadership, requiring expertise in data strategy, cloud architecture, and advanced analytics. Key responsibilities include defining enterprise-level data strategies, architecting cloud solutions, and developing predictive analytics models to enhance athlete performance and fan engagement. The ideal candidate will have extensive experience in data architecture and a strong understanding of the sports industry's dynamics.