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Senior Data Science Analyst
Sally Beauty. Develop, validate, deploy, and monitor machine learning models for acquisition, retention, churn reduction, customer lifetime value, segmentation, propensity scoring, and next-best-action recommendations .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying machine learning models, customer analytics, and data-driven strategies to enhance customer engagement and retention. Proficient in utilizing advanced statistical methodologies and tools to derive actionable insights and optimize marketing initiatives.
Highest-signal resume keywords
Machine Learning Model DevelopmentAdvanced Proficiency In PythonSQL Data Extraction And AnalysisExperience With Databricks And PySparkStatistical Analysis And Experimental Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData AnalysisFeature EngineeringPredictive ModelingRegression AnalysisClassificationClusteringA/B TestingData Pipeline DevelopmentMLOps
Soft Skills
Analytical ThinkingProblem-SolvingBusiness AcumenCommunicationTime Management
Tools & Technologies
DatabricksSQLPython Libraries (Pandas, NumPy, Scikit-learn)MLflowMicrosoft Azure
Industry Keywords
Customer AnalyticsEcommerceRetailConsumer Packaged GoodsLoyalty Programs
Tech Stack
Tools & technologiesAzureCloudNumpyPandasPySparkPythonScikit-LearnSparkSQL
About the role
Key responsibilities & impact- Develop, validate, deploy, and monitor machine learning models for acquisition, retention, churn reduction, customer lifetime value, segmentation, propensity scoring, and next-best-action recommendations
- Design and implement customer segmentation strategies using behavioral, transactional, demographic, and value-based data
- Apply statistical and machine learning methodologies to identify business opportunities
- Conduct exploratory data analysis, feature engineering, model evaluation, and validation
- Develop customer-focused analytics and predictive assets for CRM campaigns, loyalty initiatives, and customer lifecycle management
- Build and maintain scalable customer data pipelines and customer 360 solutions in Databricks using Python, PySpark, and SQL
- Convert analytical prototypes into scalable, reliable, maintainable production solutions
- Implement MLOps processes including automated scoring, retraining, performance monitoring, drift detection, and data quality validation
- Follow version control, peer code review, testing, and CI/CD practices
- Design, execute, and analyze A/B tests and multivariate experiments across email, SMS, push notifications, and mobile applications
- Develop statistically valid test and control audiences to measure campaign effectiveness and incremental impact
- Partner with CRM and Marketing teams to optimize onboarding, growth, retention, and reactivation customer journeys
- Translate complex analytical findings into business recommendations
- Present insights, forecasts, and recommendations to senior leadership and cross-functional partners
- Support ad hoc analyses, strategic initiatives, and special projects
Requirements
What you’ll need- 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 regression, classification, clustering, tree-based models, boosting algorithms, survival analysis, recommender systems, and dimensionality reduction
- Knowledge of statistics, experimental design, hypothesis testing, confidence intervals, cross-validation, probability, and predictive modeling
- Experience deploying, monitoring, and maintaining production machine learning solutions using MLflow or similar frameworks
- Knowledge of Git, code reviews, testing methodologies, and CI/CD processes
- Strong proficiency in Microsoft Excel and PowerPoint
- Ability to manage multiple priorities and deliver high-quality analytical solutions in a fast-paced environment
- Exceptional analytical thinking, problem-solving, and business acumen
Benefits
Comp & perks- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Paid vacation days
- Paid sick days
- Paid holidays
- Tuition reimbursement
- 401(k) with company match
- Complimentary in-house salon services
- Food options at the corporate campus
- Onsite Sally Beauty and CosmoProf Professional stores
- Merchandise discount