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VP Data

Talent IntegrationHerzliya, Tel Aviv District, IsraelNot specifiedFull-timeSeniority: Not specified

Posted 27 days ago · 0 applicants

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The role in plain words

Must-have
  • 8+ years of experience in Data Science and Machine Learning
  • 3+ years of experience directly managing and scaling high-performing data teams
  • Exceptional hands-on capabilities to build models and architect systems
  • Python
  • PyTorch
Nice-to-have

    Extracted from the job description · kept up to date automatically

    Who this suits

    Full job description

    Original listing · kept for reference

    Wanted: VP Data for a SaaS company in Herzliya. This is a very rewarding full-time and Hybrid position.

    The chosen candidate will spearhead the entire data function, uniquely combining strategic leadership with hands-on model building in a cutting-edge Generative AI ecosystem. This senior role offers the exciting opportunity to scale a world-class team from an early stage while directly impacting the intersection of advanced technology and the sports industry. It is a perfect match for a technical leader who thrives on architecting complex systems and possesses a massive, genuine passion for sports.

    Job Responsibilities:

    ● Own the technical direction and the end-to-end data stack, acting as a hands-on leader to build advanced multi-model deep learning and LLM/agent systems. ● Build, mentor, and scale a world-class data team while establishing a high bar for technical quality, execution, and seamless cross-functional collaboration.

    ● Partner closely with Product and Engineering to translate complex sports scouting and analytics needs into a coherent, scalable technical roadmap.

    ● Implement rigorous validation practices, establishing metrics that measure machine learning models against real-world outcomes rather than theoretical performance.

    Job Requirements:

    ● 8+ years of experience in Data Science and Machine Learning, with at least 3+ years of experience directly managing and scaling high-performing data teams.

    ● Exceptional hands-on capabilities to build models and architect systems, backed by strong proficiency in Python and modern ML tooling (such as PyTorch, Pandas, and NumPy).

    ● Deep understanding of deep learning fundamentals, production deployment, and robust data engineering pipelines (ETL, SQL, and processing messy real-world datasets).

    ● Proven experience in building, evaluating, and deploying LLM- and agent-based systems within a production environment.

    ● A huge passion for sports and sports analytics; previous experience working in sports companies or possessing deep football domain knowledge is a major advantage.

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    Talent Integration
    Posted 27 days ago · 0 applicants
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