Senior Director Data Science
Lowell, MA, US
- Pay
- Pay not listedSimilar roles state $153K–$225K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
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- Sponsorship
Visa sponsorship not confirmed — sponsorship source
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. AI & Machine Learning Delivery 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. Product & Customer Impact 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. Operational Excellence 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. UKG is unable to offer sponsorship for this position. 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. 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. Strategic thinking and business acumen Executive communication and influence Organizational design and talent development Data-driven decision making Customer-centric innovation Cross-functional collaboration Operational rigor and execution excellence Delivery against strategic roadmap commitments
Read the full posting
What you’ll work on
Full postingDefine the multi-year data science and AI strategy and investment priorities
Lead development of predictive, prescriptive, and generative AI solutions
Partner with engineering to operationalize models at scale via MLOps
Ensure monitoring, evaluation, and continuous improvement of deployed models
Build, develop, and retain a team of data scientists, ML engineers, and managers
From the employer’s posting
Define and execute the multi-year data science and AI strategy aligned with company objectives.
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.
Build, develop, and retain a world-class team of data scientists, machine learning engineers, and managers.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 25, 2026 · 67 days ago
- Recorded sightings
- 327
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
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- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on apply.ukg.com. The employer’s form will show what is required.
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Job description
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. AI & Machine Learning Delivery 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. Product & Customer Impact 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. Operational Excellence 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. UKG is unable to offer sponsorship for this position. 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. 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. Strategic thinking and business acumen Executive communication and influence Organizational design and talent development Data-driven decision making Customer-centric innovation Cross-functional collaboration Operational rigor and execution excellence Delivery against strategic roadmap commitments
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Lowell, MA, US
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