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Job description
Join Sally Beauty Supply LLC as a Data Scientist in Plano, TX (onsite) and help turn customer data into machine learning models that improve Customer Lifetime Value (CLV) . You will build and operate end-to-end analytics and ML solutions in Databricks , supporting hyper-personalized CRM, retention, and proactive churn reduction. You will also translate model outputs into clear, actionable recommendations for non-technical senior leadership .
This role includes a competitive salary of USD 100,000 - 120,000 per year , along with a benefits package designed to support day-to-day life and long-term security.
What you’ll do
Develop machine learning models across the full lifecycle including design, feature engineering, training, evaluation, validation, and implementation using Python .
Drive high-impact customer analytics use cases such as churn and retention modeling , propensity-to-buy , CLV prediction , customer persona/segmentation , and next-best-action recommendations .
Build segments beyond demographics using behavioral, psychographic, and value-based approaches (example methods include RFM , K-Means clustering , and propensity tiers ) so CRM and Marketing can activate them directly.
Apply advanced analytics methods including Market Basket Analysis , survival analysis , uplift/incrementality modeling , and recommender approaches to identify cross-sell, up-sell, and hidden revenue opportunities.
Produce disciplined analysis with summary statistics , distribution and correlation studies , and appropriate feature selection using confidence intervals and validation techniques such as cross-validation and model performance checks.
Deliver priority ad hoc analysis that supports the SALLY plan and forecast , balancing speed with statistical accuracy.
Own customer data foundations by building and maintaining a customer 360 view and data pipelines in Databricks using Python, PySpark, and SQL .
Convert proof-of-concept work into production-ready, reusable components integrated into products and services, with attention to scalability (compute, memory, I/O, model serialization, caching).
Automate ML operations such as scheduled scoring and model re-training , and implement monitoring for data drift , model drift , and accuracy degradation , including back-testing, explainability, reproducibility, and data quality checks.
Support analytics engineering practices including source control , peer code review , and automated testing using Git and Azure DevOps , contributing to CI/CD for analytics assets.
Design and analyze A/B and multivariate tests for email, SMS, push, and in-app campaigns to optimize engagement, conversion, and incremental lift, including statistically sound test and control audiences.
Execute measurement frameworks for test vs. control and apply guardrails for attribution , incrementality , and performance readouts.
Maintain SOPs for campaign measurement, reporting hygiene, and data integrity, and support customer journeys across Onboarding, Growth, Retention, and Reactivation .
What you’ll bring
Master’s degree in mathematics / Statistics / Data Science and Analytics, Computer Science, Economics, Physics, or a related field (required). Master’s degree preferred.
4+ years of hands-on experience in data science, applied machine learning, or customer analytics.
Advanced proficiency in Python (pandas, NumPy, scikit-learn) and SQL .
Experience with Databricks , Spark/PySpark , Delta Lake , and a major cloud environment (Azure preferred; AWS/GCP acceptable).
Working knowledge of regression, classification, clustering (K-Means) , tree-based and boosting methods , survival analysis , recommender systems , and dimensionality reduction (PCA) .
Exposure to hypothesis testing , confidence intervals , experimental design , cross-validation , and basic probability and linear algebra.
Experience with model deployment and monitoring (for example, MLflow ), model re-training automation, drift detection, Git , and code review practices.
Solid PowerPoint and Excel skills to communicate executive-ready narratives.
Helpful extras: R experience, exposure to deep learning frameworks, and familiarity with REST APIs, containerization, or orchestration tooling.
Tools you’ll use
Python, pandas, NumPy, scikit-learn, SQL, R, Databricks, Spark, PySpark, Delta Lake, Azure, AWS, GCP, MLflow, Git, Azure DevOps, REST APIs
Benefits
Competitive salary and outstanding benefits package
Medical , Dental , and Vision
Life Insurance
Paid vacation and sick days and paid holidays
Tuition reimbursement
401(k) with company match
In-house salon with complementary services
Varied selection of food options at the corporate center
Working conditions
Hybrid role requiring onsite presence at the corporate office on specified days.
Work environment generally involves everyday risks or discomforts typical of offices, meeting and training rooms, retail stores, and residences or commercial vehicles, with normal safety precautions.
Sedentary work; may include some walking, standing, bending, and occasional need to carry, move, and set up small hardware such as desktops, monitors, printers, and testing lab equipment.
Work area is adequately lit, heated, and ventilated.
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Worksite address
plano, TX, 75086, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.