Head of Data Science

W Talent

Texas

Presencial

USD 120.000 - 150.000

Jornada completa

14 días+

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Descripción de la vacante

A leading financial services organization in Wisconsin is seeking a seasoned leader for its new Data Science function. This role is crucial in advancing enterprise-level AI and data science initiatives. The candidate should have over 5 years of leadership experience and 10 years in data management, along with strong expertise in AWS and Snowflake. This position offers a unique opportunity to shape the organization’s AI strategy while leading a high-performing data team.

Formación

  • 5+ years of leadership experience in data science.
  • 10+ years in data management focusing on AI and ML.
  • Strong understanding of data engineering practices.

Responsabilidades

  • Drive enterprise AI and data science strategy and delivery.
  • Provide leadership and direction to a data team.
  • Ensure strong governance and modern engineering practices.

Conocimientos

Leadership experience
Data management
AI/ML expertise
Cloud computing knowledge
Data engineering exposure

Herramientas

AWS
Snowflake

Descripción del empleo

I’m supporting a leading financial services organization that is investing heavily in an AI-first strategy and building out a brand-new Data Science function. This is an opportunity to shape enterprise-level AI, ML, and data capabilities.

This role will play a pivotal role in scaling AI and data science initiatives across the business. The position blends strategic leadership (70%) with hands‑on influence (30%), while leading a team.

Responsibilities
  • Drive enterprise AI and data science strategy and delivery
  • Oversee development of advanced analytics, ML models, and cloud‑based solutions
  • Provide leadership, coaching, and direction to a high‑performing data team
  • Partner with senior stakeholders to advance the organization’s AI‑first vision
  • Ensure strong data foundations, governance, and modern engineering practices
Requirements
  • 5+ years of leadership experience
  • 10+ years in data management with depth in data science, AI/ML, and cloud
  • Strong exposure to data engineering, even if not the primary focus
  • Expertise in AWS and Snowflake
  • Background in financial services, insurance, or banking
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