Executive Director - Data Management, Analytics, AI & Architecture

Regeneron

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Sleepy Hollow, NY
Salary
$255,000–$424,900 / yr
Posted
16 days ago
Freshness
Confirmed live 2 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $241k
This role $340k
$153k most similar roles pay here $454k

This role pays more than 93% of similar roles. Most pay $204,843–$278,000 — the shaded band above. At the midpoint, this role pays about $340k versus about $241k for comparable roles.

Based on 240 similar postings.

Employer

About Regeneron

Regeneron is a leading science-driven biotechnology company that invents, develops, and commercializes life-transforming medicines for serious diseases.

Regeneron currently has 18 open roles on FindRole.

Listed pay typically runs $141,100–$243,350 across 18 roles with salary data.

Most-posted roles

View all roles at Regeneron

At a glance

TL;DR · Executive Director - Data Management, Analytics, AI & Architecture

Role Posting Log in to save

Executive Director - Data Management, Analytics, AI & Architecture leads the strategy for commercial and G&A data capabilities to transform enterprise data into trusted insights. This leader manages a high-performing team of professionals to build scalable data architecture, analytics products, and self-service capabilities for departments including Finance, HR, and Procurement. The role involves establishing enterprise-wide governance, master data standards, and lifecycle management while modernizing the ecosystem through cloud platforms and integration strategies. Key responsibilities include advancing AI, machine learning, and automation while ensuring responsible AI practices and regulatory compliance in a regulated industry context. Required expertise includes deep command of business intelligence, data modeling, and reference architecture standards. The candidate will navigate complex data security, vendor partnerships, and risk frameworks to drive operational efficiency and measurable business outcomes across global teams.

Skills

Data Management Data Architecture Analytics AI Machine Learning Master Data Management Data Governance Cloud Platforms Business Intelligence Data Modeling Automation GxP NIST AI RMF ISO 42001 Data Quality

What you'll do

  • Execute the multi-year data management, analytics, AI, and enterprise architecture strategy for Commercial and G&A functions.
  • Lead and develop a high-performing team of data management, analytics, and architecture professionals.
  • Deliver trusted data platforms, analytics products, and self-service capabilities to empower business leaders.
  • Establish enterprise-wide data governance, stewardship, quality, lifecycle management, and master data standards.
  • Modernize the data ecosystem through scalable cloud platforms, integration strategies, and architecture standards.
  • Advance AI, machine learning, and automation by identifying high-value use cases while ensuring regulatory compliance.
  • Drive measurable business outcomes through improved data quality, analytics adoption, and process standardization.
  • Oversee vendor partnerships, data security, and architecture governance to ensure strategic investment value.

What we're looking for

  • A BS/BA in Computer Science, Data Science, Information Systems, or a related field is required.
  • An MS, PhD, or MBA is preferred.
  • Candidates must have 17+ years of progressive leadership in data management, architecture, analytics, or business intelligence.
  • Experience in life sciences, biotechnology, or other regulated industries is preferred.
  • Candidates must possess deep command of modern data management, analytics, and enterprise architecture capabilities.
  • Experience establishing enterprise data governance frameworks and reference architecture standards is required.
  • Candidates must have a strong understanding of AI, machine learning, and responsible AI practices at scale.
  • Familiarity with regulatory and risk frameworks for AI in regulated industries is preferred.

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