Head of Data Science

W Talent; Town of Texas (WI); On-site; USD 120,000 - 150,000; Full time

Job summary

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.

Qualifications

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

Responsibilities

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

Skills

Leadership experience

Data management

AI/ML expertise

Cloud computing knowledge

Data engineering exposure

Tools

AWS

Snowflake

Job description

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