Data Scientist — CRM ML & Customer Insights

Sally Beauty; Plano (TX); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401(k) with company match

Tuition reimbursement

Paid vacation and sick days

Job summary

Sally Beauty Holdings, Inc. seeks a hands-on Data Scientist (Corporate) to build models and data products powering customer insights and activation.

You will own end-to-end ML pipelines from feature engineering to deployment, collaborating with Data Engineering, CRM, Marketing, and Merchandising to mature Databricks-based platforms. The role focuses on increasing Customer Lifetime Value through hyper-personalized campaigns, retention strategies, and churn reduction, delivering production-grade

Qualifications

• Master's degree in mathematics / statistics / data science and analytics, computer science, economics, physics, or related field required; master's preferred.
• 4+ years of hands-on data science, applied ML, or customer analytics experience.
• Experience in Retail, CPG, e-commerce, or loyalty-driven businesses is highly desirable.

Responsibilities

• Build machine learning models across development, training, validation, and deployment using Python; focus on churn, retention, CLV, segmentation, and recommended actions.
• Develop customer segmentation using behavioral and value-based approaches (e.g., RFM, clustering).
• Apply MBA, survival analysis, uplift modeling, and recommender systems to identify revenue opportunities.
• Ensure statistical rigor with validation, cross-validation, and data quality checks; productionize analytics assets.

Skills

Python

SQL

ML

Feature engineering

Education

Master's degree in mathematics / statistics / data science and analytics

Tools

Databricks

PySpark

Delta Lake

Azure

Python

SQL

Job description

Sally Beauty Holdings, Inc. seeks a hands-on Data Scientist (Corporate) to build models and data products powering customer insights and activation.

You will own end-to-end ML pipelines from feature engineering to deployment, collaborating with Data Engineering, CRM, Marketing, and Merchandising to mature Databricks-based platforms. The role focuses on increasing Customer Lifetime Value through hyper-personalized campaigns, retention strategies, and churn reduction, delivering production-grade