Sr Director Data Science

UKG•Lowell, MA

17h•$233,300 - $335,400

About The Position

The Senior Director of Data Science leads the strategy, execution, and operationalization of data science and machine learning initiatives across the organization. This leader is responsible for building high-performing data science teams, defining the AI and analytics roadmap, and partnering with Engineering, Product Management, Design, and Business stakeholders to deliver measurable customer and business outcomes. This role serves as a key member of the AI leadership team, driving innovation in predictive modeling, generative AI, responsible AI practices, experimentation, and large-scale machine learning platforms.

Requirements

Master's degree or PhD in Computer Science, Data Science, Statistics, Mathematics, Operations Research, or a related field.
12+ years of experience in data science, analytics, AI, or machine learning.
5+ years of senior leadership experience managing managers and large technical organizations.
Proven experience delivering machine learning systems into production at enterprise scale.
Strong understanding of statistical modeling, experimentation, predictive analytics, and AI technologies.

Nice To Haves

Experience partnering with executive leadership on business and technology strategy.
Experience with Generative AI, LLMs, AI agents, and AI platform ecosystems.
Experience building AI-powered SaaS products.
Familiarity with workforce management, HR technology, enterprise software, or related domains.
Experience establishing Responsible AI and AI governance programs.
Track record of leading organizational transformation through data and AI.

Responsibilities

Define and execute the multi-year data science and AI strategy aligned with company objectives.
Identify high-value business and customer problems that can be solved through machine learning, analytics, and AI.
Establish data science operating models, governance standards, and success metrics.
Drive prioritization of investments across research, experimentation, and production AI capabilities.
Lead development of predictive, prescriptive, and generative AI solutions.
Partner with engineering teams to operationalize models at scale through MLOps and AI platform capabilities.
Ensure robust monitoring, observability, evaluation, and continuous improvement of deployed models.
Champion responsible AI practices including fairness, explainability, privacy, security, and compliance.
Collaborate with Product Management to define AI-powered product experiences and roadmap priorities.
Translate customer needs into data science opportunities that improve business outcomes.
Establish mechanisms for measuring customer value, adoption, and ROI from AI investments.
Support strategic customer engagements and executive discussions involving AI capabilities.
Build, develop, and retain a world-class team of data scientists, machine learning engineers, and managers.
Establish career frameworks, hiring strategies, and talent development programs.
Mentor leaders and create a culture of innovation, accountability, and operational excellence.
Promote collaboration across engineering, research, product, and go-to-market teams.
Define metrics and reporting frameworks to measure model quality, business impact, and platform efficiency.
Drive planning, budgeting, staffing, and execution across multiple concurrent initiatives.
Ensure effective risk management and governance for AI and data-driven systems.
Lead reviews of architecture, experimentation frameworks, and technical direction.