Sr. Data Science Analyst

Job Description

Senior Data Science Analyst (Corporate)

This position is Hybrid working from our Legacy West Support Center located in Plano, Texas.

About the Role

The Senior Data Science Analyst is a hands-on technical contributor responsible for building predictive models, advanced analytics solutions, and production-ready data products that help Sally Beauty Holdings better understand and activate customer behavior. This role combines data science, machine learning, statistical analysis, and data engineering to drive customer acquisition, retention, engagement, and lifetime value initiatives.

Working at the intersection of advanced analytics and commercial strategy, the Senior Data Science Analyst partners closely with Customer Analytics, CRM, Marketing, Merchandising, and Data Engineering teams to develop scalable models and insights that support hyper-personalized customer experiences. This role owns the end-to-end lifecycle of data science initiatives, including problem definition, feature engineering, model development, validation, deployment, monitoring, and ongoing optimization.

Responsibilities

• Develop, validate, deploy, and monitor machine learning models that support customer acquisition, retention, churn reduction, customer lifetime value (CLV), segmentation, propensity scoring, and next-best-action recommendations.
• Design and implement advanced customer segmentation strategies using behavioral, transactional, demographic, and value-based data.
• Apply statistical and machine learning methodologies including clustering, regression, classification, survival analysis, recommender systems, and market basket analysis to identify business opportunities.
• Conduct exploratory data analysis, feature engineering, model evaluation, and validation to ensure high-quality and statistically sound outcomes.
• Develop customer-focused analytics and predictive assets that support CRM campaigns, loyalty initiatives, and customer lifecycle management strategies.
• Build and maintain scalable customer data pipelines and customer 360 solutions within Databricks using Python, PySpark, and SQL.
• Convert analytical prototypes into production-ready solutions with a focus on scalability, reliability, maintainability, and business impact.
• Implement and maintain MLOps processes including automated model scoring, retraining, performance monitoring, drift detection, and data quality validation.
• Follow software engineering best practices including version control, peer code review, testing, and CI/CD deployment processes.
• Design, execute, and analyze A/B tests and multivariate experiments across digital marketing channels including email, SMS, push notifications, and mobile applications.
• Develop statistically valid test and control audiences to support accurate measurement of campaign effectiveness and incremental business impact.
• Partner with CRM and Marketing teams to optimize customer journeys including onboarding, growth, retention, and reactivation programs.
• Translate complex analytical findings into clear business recommendations for technical and non-technical stakeholders.
• Present insights, forecasts, and recommendations to senior leadership and cross-functional partners.
• Support ad hoc analyses, strategic initiatives, and special projects that advance customer and business objectives.

Knowledge, Skills & Abilities Requirements

• Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Physics, Analytics, or a related quantitative field preferred.
• 4+ years of experience in data science, machine learning, customer analytics, or advanced analytics roles.
• Experience within retail, ecommerce, consumer packaged goods (CPG), loyalty, subscription, or customer-focused industries preferred.
• Advanced proficiency in Python, including pandas, NumPy, scikit-learn, and related data science libraries.
• Advanced proficiency in SQL for data extraction, transformation, and analysis.
• Experience with Databricks, Spark/PySpark, Delta Lake, and cloud-based analytics environments, preferably Microsoft Azure.
• Strong understanding of machine learning techniques including regression, classification, clustering, tree-based models, boosting algorithms, survival analysis, recommender systems, and dimensionality reduction methods.
• Solid foundation in statistics, experimental design, hypothesis testing, confidence intervals, cross-validation, probability, and predictive modeling.
• Experience deploying, monitoring, and maintaining production machine learning solutions using tools such as MLflow or similar frameworks.
• Knowledge of software development best practices including Git, code reviews, testing methodologies, and CI/CD processes.
• Strong proficiency in Microsoft Excel and PowerPoint with the ability to communicate analytical findings through executive-ready presentations.
• Ability to manage multiple priorities and deliver high-quality analytical solutions in a fast-paced environment.
• Exceptional analytical thinking, problem-solving, and business acumen.

Competencies & Attributes

• Passionate Learner - Continuously seeks new knowledge, embraces feedback, and applies learning to improve analytical capabilities, business outcomes, and operational processes.
• Flexible & Agile Adapter - Thrives in evolving environments, navigates ambiguity effectively, and adjusts priorities to meet changing business needs.
• Effective Communicator - Communicates technical concepts, analytical findings, and business recommendations clearly to audiences of varying technical expertise.
• Team Builder - Collaborates effectively across functions, shares knowledge, and contributes to a culture of inclusion, partnership, and continuous improvement.
• Customer Focused Partner - Uses customer insights and analytics to improve the customer experience, support business decisions, and drive measurable results.
• Strategic Thinker - Connects analytical findings to broader business objectives and identifies scalable, data-driven opportunities for growth.
• Big Picture Thinker - Understands how customer analytics, marketing, merchandising, and technology initiatives work together to drive business performance.
• Results Driver - Demonstrates accountability, prioritizes high-impact work, and consistently delivers quality outcomes that support organizational goals.
• Problem Solver & Decision Maker - Applies data, statistical rigor, and business judgment to solve complex challenges and make informed recommendations.
• Data Innovator - Actively seeks new methodologies, technologies, and analytical approaches to improve predictive capabilities and business performance.

Working Conditions & Physical Requirements

This will be a hybrid role required to be onsite at the corporate office on specified days. The work environment generally involves everyday risks or discomforts which require normal safety precautions typical of such places as offices, meeting and training rooms, retail stores, and residences or commercial vehicles, including the use of standard office equipment and adherence to workplace safety practices. The work area is adequately lit, heated, and ventilated.

The work is sedentary. Typically, the employee may sit comfortably to perform the work. However, there may be occasional walking, standing, bending, and lifting or carrying light office equipment and materials as needed.

Benefits

We offer a competitive salary and outstanding benefits package that includes medical, dental, vision, life insurance, paid vacation and sick days, paid holidays, tuition reimbursement and 401(k) with company match. In addition, associates of SBH may take advantage of our in-house salon with complimentary services and a varied selection of food options at our corporate campus. Also featured at our corporate campus is both a Sally Beauty and CosmoProf Professional onsite store, where associates enjoy a great merchandise discount!