Sr Manager, Data Science

Ulta Beauty, Inc. • Bolingbrook, IL

4d

About The Position

The Sr. Manager, Data Science is a senior people and technical leader responsible for the performance, capability, delivery, and health of the Data Science and Machine Learning capability pillar within Ulta Beauty’s Enterprise AI team. The role turns business and technology strategy into integrated priorities, operating plans, resource choices, and measurable outcomes across teams. It leads through managers and/or senior technical professionals, builds organizational capability, manages cross-team dependencies and investment trade-offs, and establishes mechanisms for consistent execution at scale. The leader partners with senior Technology, Product, and business stakeholders to shape roadmaps and decisions, strengthen the organization, and drive modernization, responsible innovation, and sustainable performance.

The position leads and develops a team of Data Scientists working across multiple projects. It combines people leadership with hands-on technical contribution when needed, including writing code and addressing complex problems. The role supports team development, removes blockers, and creates the conditions for Data Scientists to do their best work.

Requirements

• Bachelor’s degree in a highly quantitative field such as Mathematics, Statistics, Data Science, Computer Science, Engineering, or Information Systems, or equivalent experience.
• 10+ years of progressive technology experience in Data Science and Machine Learning, including significant people-leadership responsibility in complex environments.
• Strong knowledge of Data Science and AI practices, technologies, methods, and operating considerations, including multivariate regression, statistical inference, supervised and unsupervised learning, LLMs, and RAG.
• Proficiency in Python and scientific frameworks such as Scikit-Learn, NumPy, and SciPy.
• Hands-on experience with Databricks and enterprise cloud platforms.
• Demonstrated experience leading technical teams, managers, senior technical professionals, or a significant technical domain.
• Ability to translate strategy into integrated priorities, operating plans, capacity decisions, and measurable outcomes across teams.
• Experience managing cross-team dependencies, organizational change, significant technical or operational risk, and complex stakeholder trade-offs.
• Talent-leadership capability, including manager development, succession planning, performance management, hiring, workforce planning, and organizational capability building.
• Experience managing or materially influencing budgets, vendors or partners, capacity, and technology investment trade-offs.
• Ability to influence senior technical, product, business, and leadership stakeholders without relying solely on formal authority.
• Strong business judgment, analytical thinking, communication, and executive-level storytelling skills.
• Ability to scale modern technical practices, automation, and responsible AI-enabled ways of working across teams.

Nice To Haves

• Experience with GCP, the preferred enterprise cloud platform.

Responsibilities

• Lead, coach, and develop a high-performing team of Data Scientists; set technical expectations, provide feedback, and create development plans.
• Provide hands-on Data Science and Machine Learning expertise through solution design, code reviews, model troubleshooting, and complex technical problem-solving.
• Establish and enforce best practices for coding, version control, peer reviews, experimentation, model validation, documentation, and responsible AI.
• Elevate modeling rigor by challenging technical approaches and coaching teams on statistical inference, experimentation, causal reasoning, and model evaluation.
• Guide end-to-end Data Science development, from problem framing and data preparation through feature engineering, algorithm selection, evaluation, deployment, and monitoring.
• Own delivery and technical quality across concurrent Data Science initiatives, remove blockers, build models, and drive adoption toward measurable outcomes.
• Deliver production-ready, scalable Data Science solutions that include testing, and partner with Operations to enable monitoring and ongoing model maintenance.
• Explain technical approaches, results, and trade-offs to senior business and technology stakeholders; influence decisions and define clear measures of success.
• Partner with Product, Operations, Engineering, and business leaders across departments to identify opportunities, translate business challenges into Data Science solutions, and influence priorities.
• Drive technical upskilling through mentorship, structured learning, workshops, and regular knowledge sharing on modern methods and tools.
• Stay informed about emerging Data Science and AI techniques and best practices, and partner with leadership to identify innovative use cases.
• Promote an analytics-driven culture and contribute to enterprise AI capabilities and platforms.

Benefits

• Eligible associates may earn additional compensation under the Company’s bonus plan.
• Full-time positions are eligible for paid time off.
• Full-time positions are eligible for health, dental, vision, life, and disability benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager