Senior Data Science Analyst - Customer Analytics (Hybrid)

Cosmoprof; Plano (TX); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

Paid vacation and sick days

Tuition reimbursement

401(k) with company match

Onsite salon discount

Job summary

Sally Beauty Holdings, Inc. seeks a Senior Data Science Analyst (Corporate) to drive predictive analytics and data-driven decision making. This role combines data science, ML, and data engineering to support acquisition, retention, and lifecycle initiatives.

You will collaborate with CRM, Marketing, Merchandising, and Data Engineering teams to deploy scalable models and insights, owning end-to-end lifecycle from problem definition to deployment and monitoring.

Qualifications

• Master’s degree in Data Science, Statistics, or a related quantitative field preferred.
• 4+ years of data science, machine learning, or advanced analytics experience.
• Experience in retail/ecommerce or customer analytics is a plus.
• Proficiency in Python (pandas, NumPy, scikit-learn) and SQL.

Responsibilities

• Develop, validate, deploy, and monitor ML models for customer analytics and lifecycle management.
• Design and implement advanced customer segmentation strategies using diverse data.
• Apply ML methods (regression, classification, clustering, survival analysis, recommender systems) to identify opportunities.
• Build scalable data pipelines and 360-degree customer views in Databricks using Python, PySpark, and SQL.
• Translate analytical findings into business recommendations for stakeholders.

Skills

Python

SQL

Machine Learning

Statistics

Data storytelling

Big data

Education

Master’s degree in Data Science or related

Tools

Databricks

Spark/PySpark

Azure

MLflow

Git

Job description

Sally Beauty Holdings, Inc. seeks a Senior Data Science Analyst (Corporate) to drive predictive analytics and data-driven decision making. This role combines data science, ML, and data engineering to support acquisition, retention, and lifecycle initiatives.

You will collaborate with CRM, Marketing, Merchandising, and Data Engineering teams to deploy scalable models and insights, owning end-to-end lifecycle from problem definition to deployment and monitoring.