Data Scientist

OVERVIEW

Live the experience . From professional empowerment to continual learning opportunities. From ongoing investment in new and emerging technologies to a career of self-determination. At Ulta Beauty, our tech team is critical to our scalability—and is recognized that way. We’ve been defined as a “mature start-up.” A place where interdepartmental exposure, open doors, and genuine collaboration is ubiquitous. Where challenges come fast and furious, requiring agility, mental dexterity, and creativity. Where our passion for better solutions drives us and is core to who we are.

We’re engineering for the future of retail, and it’s no-holds-barred. But for those motivated by continual change and ambiguity, by superior leadership, by whip smart colleagues who will press you daily for your very best, you’ll find that virtually nothing’s impossible at Ulta Beauty.

THE IMPACT YOU CAN MAKE:

This Data Scientist is an integral part of the Data Science and Machine Learning practice within our Enterprise AI team at Ulta Beauty. This team utilizes the power of data science and machine learning techniques to address the diverse business questions and challenges facing Ulta Beauty. As a Data Scientist, you will succeed by mining our rich data assets to develop features, conducting statistical analyses, building DS/ML models, and constructing large scale prediction systems in a fast-paced, data-focused retail environment. The Data Scientist will also act as a subject matter expert, communicating the value and tackling the application of advanced analytics for various use cases with multiple stakeholders across Ulta Beauty.

YOU'LL ACCOMPLISH THESE GOALS BY:

• Design and develop data science and machine learning models to optimize operational tactics, marketing messages, and guest experiences, while generating efficiencies across Ulta Beauty
• In addition to classical statistical methods, research and implement new machine learning approaches and techniques to drive innovative solutions that solve business problems
• Mine our rich, omnichannel, customer data assets across 1500+ stores, a leading e-commerce platform, and 46M+ Ultamate Rewards loyalty program members to construct analytical solutions that enable data-driven decisions
• Partner with the AI Engineering and Architecture peers, contributing the Data Science perspective in cross-functional discussions
• Engage with business and product stakeholders to refine requirements into a concrete, technical scope
• Explain and present complex analytical approaches and model results in a concise manner to drive alignment and outcomes from business partners
• Ensure data integrity and quality by leveraging proven methodologies, including data reconciliation, data integration and data audits
• Continue driving a data-driven culture and contribute to the creation of enterprise AI capabilities and platforms that power Ulta Beauty’s future

ESSENTIALS FOR SUCCESS:

• 2+ years of professional experience in data science, machine learning, or analytics functions, with a track record of owning and delivering work in a production environment
• Advanced degree in a highly quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, etc. Equivalent professional experience will be considered.
• In-depth knowledge and experience with data science and machine learning concepts (e.g., multivariate regression, statistical inference, supervised and unsupervised learning, etc.)
• Proficiency in Python and scientific related frameworks (e.g., Scikit-Learn, NumX, SciPy etc.)
• Hands‑on experience designing, deploying, and maintaining machine learning pipelines
• Excellent interpersonal, verbal, and written communication skills to communicate complex ideas to various audiences in both a technical and user-friendly language
• Demonstrated ability to work effectively both in a team environment and independently by handling multiple projects, meeting deadlines, prioritizing appropriately and responding to issues quickly and creatively with an open and positive attitude
• Energetic and self‑motivated with a strong sense of curiosity - must be extremely organized and detail oriented with an ability to make proactive recommendations
• Passion for broadening your technical skills and diving into unknown problems

PREFERRED QUALIFICATIONS:

• Hands‑on experience working in Databricks and enterprise cloud platforms, preferably GCP
• Practical experience with CI/CD and MLOps best practices and tools (Git, Airflow, MLflow, Jenkins, etc.)
• Experience with Apache Spark (PySpark, and Spark ML) and/or deep learning frameworks (e.g., Tensorflow, Torch, etc.)
• Understanding of causal and uplift models
• Prior work in retail, e-commerce, or consumer-facing technology environments

The pay range for this position is $102,900.00 - $130,000.00 / Year with the opportunity for eligible associates to earn additional compensation pursuant to the Company’s bonus plan. Exact pay will be based on factors including, but not limited to relevant education, qualifications, certifications, experience, level, shift, geographic location, and business and organizational needs. Full-time positions are eligible for paid time off, health, dental, vision, life and disability benefits. Part-time positions are eligible for dental, vision, life, and disability benefits. For additional information concerning our benefits, visit our Benefits and Career Development page:

ABOUT

At Ulta Beauty (NASDAQ: ULTA), the possibilities are beautiful. Ulta Beauty is the largest North American beauty retailer and the premier beauty destination for cosmetics, fragrance, skin care products, hair care products and salon services. We bring possibilities to life through the power of beauty each and every day in our stores and online with more than 25,000 products from approximately 500 well-established and emerging beauty brands across all categories and price points, including Ulta Beauty’s own private label. Ulta Beauty also offers a full-service salon in every store featuring—hair, skin, brow, and make-up services.

We will consider for employment all qualified applicants, including those with arrest records, conviction records, or other criminal histories, in a manner consistent with the requirements of any applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act.

ESSENTIALS FOR SUCCESS:

• 2+ years of professional experience in data science, machine learning, or analytics functions, with a track record of owning and delivering work in a production environment
• Advanced degree in a highly quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, etc. Equivalent professional experience will be considered.
• In-depth knowledge and experience with data science and machine learning concepts (e.g., multivariate regression, statistical inference, supervised and unsupervised learning, etc.)
• Proficiency in Python and scientific related frameworks (e.g., Scikit-Learn, NumX, SciPy etc.)
• Hands‑on experience designing, deploying, and maintaining machine learning pipelines
• Excellent interpersonal, verbal, and written communication skills to communicate complex ideas to various audiences in both a technical and user-friendly language
• Demonstrated ability to work effectively both in a team environment and independently by handling multiple projects, meeting deadlines, prioritizing appropriately and responding to issues quickly and creatively with an open and positive attitude
• Energetic and self‑motivated with a strong sense of curiosity - must be extremely organized and detail oriented with an ability to make proactive recommendations
• Passion for broadening your technical skills and diving into unknown problems

PREFERRED QUALIFICATIONS:

• Hands‑on experience working in Databricks and enterprise cloud platforms, preferably GCP
• Practical experience with CI/CD and MLOps best practices and tools (Git, Airflow, MLflow, Jenkins, etc.)
• Experience with Apache Spark (PySpark, and Spark ML) and/or deep learning frameworks (e.g., Tensorflow, Torch, etc.)
• Understanding of causal and uplift models
• Prior work in retail, e-commerce, or consumer-facing technology environments

THE IMPACT YOU CAN MAKE:

This Data Scientist is an integral part of the Data Science and Machine Learning practice within our Enterprise AI team at Ulta Beauty. This team utilizes the power of data science and machine learning techniques to address the diverse business questions and challenges facing Ulta Beauty. As a Data Scientist, you will succeed by mining our rich data assets to develop features, conducting statistical analyses, building DS/ML models, and constructing large scale prediction systems in a fast-paced, data-focused retail environment. The Data Scientist will also act as a subject matter expert, communicating the value and tackling the application of advanced analytics for various use cases with multiple stakeholders across Ulta Beauty.

YOU'LL ACCOMPLISH THESE GOALS BY:

• Design and develop data science and machine learning models to optimize operational tactics, marketing messages, and guest experiences, while generating efficiencies across Ulta Beauty
• In addition to classical statistical methods, research and implement new machine learning approaches and techniques to drive innovative solutions that solve business problems
• Mine our rich, omnichannel, customer data assets across 1500+ stores, a leading e-commerce platform, and 46M+ Ultamate Rewards loyalty program members to construct analytical solutions that enable data-driven decisions
• Partner with the AI Engineering and Architecture peers, contributing the Data Science perspective in cross-functional discussions
• Engage with business and product stakeholders to refine requirements into a concrete, technical scope
• Explain and present complex analytical approaches and model results in a concise manner to drive alignment and outcomes from business partners
• Ensure data integrity and quality by leveraging proven methodologies, including data reconciliation, data integration and data audits
• Continue driving a data-driven culture and contribute to the creation of enterprise AI capabilities and platforms that power Ulta Beauty’s future

ESSENTIALS FOR SUCCESS:

• 2+ years of professional experience in data science, machine learning, or analytics functions, with a track record of owning and delivering work in a production environment
• Advanced degree in a highly quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, etc. Equivalent professional experience will be considered.
• In-depth knowledge and experience with data science and machine learning concepts (e.g., multivariate regression, statistical inference, supervised and unsupervised learning, etc.)
• Proficiency in Python and scientific related frameworks (e.g., Scikit-Learn, NumX, SciPy etc.)
• Hands‑on experience designing, deploying, and maintaining machine learning pipelines
• Excellent interpersonal, verbal, and written communication skills to communicate complex ideas to various audiences in both a technical and user-friendly language
• Demonstrated ability to work effectively both in a team environment and independently by handling multiple projects, meeting deadlines, prioritizing appropriately and responding to issues quickly and creatively with an open and positive attitude
• Energetic and self‑motivated with a strong sense of curiosity - must be extremely organized and detail oriented with an ability to make proactive recommendations
• Passion for broadening your technical skills and diving into unknown problems

PREFERRED QUALIFICATIONS:

• Hands‑on experience working in Databricks and enterprise cloud platforms, preferably GCP
• Practical experience with CI/CD and MLOps best practices and tools (Git, Airflow, MLflow, Jenkins, etc.)
• Experience with Apache Spark (PySpark, and Spark ML) and/or deep learning frameworks (e.g., Tensorflow, Torch, etc.)
• Understanding of causal and uplift models
• Prior work in retail, e-commerce, or consumer-facing technology environments