Belk
Decision Scientist
Charlotte, NC - Corporate Office - Merchandising
No sponsorshipDetected 6 days ago
PythonAlgorithmsSQLSnowflakeDatabricksMachine LearningData EngineeringData ScienceStatisticsA/B TestingSalesforceCRMExperimental DesignLeadershipCommunication
About the role
- These models power decisioning across owned channels including email, SMS, and push, enabling personalized, data-driven customer engagement at scale.
- Belk will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa). #LI-CM1 #IND3
Responsibilities
- Design and analyze A/B and multivariate experiments to measure model performance and continuously refine decisioning logic
- Partner with campaign operations to translate model outputs into actionable audience segments, suppression lists, and treatment assignments
- Build holdout and incrementality testing infrastructure to ensure accurate measurement of model-driven lift
- Develop deep understanding of Belk customer segments by loyalty tier, shopping occasion, and FOB affinity to ensure models reflect behavioral nuance
- Build SQL-based data pipelines to extract, transform, and prepare modeling datasets from enterprise data platforms
- Establish model monitoring, drift detection, and retraining cadences to maintain model accuracy over time
- Document model methodology, assumptions, validation results, and performance benchmarks to support governance and reproducibility
- Partner with marketing strategists and CRM leads to define decisioning use cases and prioritize the model development roadmap
- Contribute ideas and best practices within the Decision Science function, and collaborate effectively across analytics and marketing teams
Requirements
- Bachelor's Degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or related quantitative field required.
- Working knowledge of customer lifecycle dynamics and an interest in CRM and loyalty marketing applications
- Exceptional ability to communicate complex quantitative concepts to non-technical stakeholders, including marketing leadership
Nice to have
- 2-4 years applied data science, quantitative analytics, or related work
- hands-on experience with predictive modeling in an academic or professional setting required.
- Experience deploying models into production environments
- familiarity with CDP platforms (e.g., Salesforce Marketing Cloud, Adobe, Braze) a strong plus.
Skills
- Expert-level proficiency in Python and/or R for statistical modeling, machine learning, and data manipulation
- Knowledge, Skills & Abilities:
- Strong SQL skills for complex data extraction and feature engineering from large enterprise datasets
Benefits
- Awareness of or exposure to reinforcement learning, multi-armed bandit, or contextual bandit approaches; willingness to develop deeper expertise
Visa & Work Authorization
- Belk will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa). #LI-CM1 #IND3
This listing is sourced directly from Belk's careers page and normalized into a canonical job model.