Senior Platform AI Enablement & Data Science Manager

academy; Katy (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Academy Sports + Outdoors is seeking a senior data science leader to define and evolve reusable data, feature, and modeling patterns, as well as MLOps and production-ready analytics solutions. You will partner with CIO Data Engineering and Platform teams to influence data models, datasets, and data access standards.

The role requires translating customer and omnichannel needs into scalable patterns, enabling data scientists, analysts, and engineers to adopt standards and accelerate delivery.

Qualifications

• Bachelor's degree in engineering, statistics, data science, or computer sciences.
• Master's degree in analytics or data science preferred.
• 8+ years in data science, advanced analytics, ML, or related fields; retail/B2C preferred.
• 4+ years leading teams or major technical initiatives; people management or matrixed leadership.
• 3+ years in B2C, retail, e-commerce, marketing analytics, or customer-facing analytics.
• 3+ years deploying production-grade analytics or ML solutions.

Responsibilities

• Define and evolve reusable data, feature, and modeling patterns.
• Lead MLOps and production-ready analytics solutions across platforms.
• Translate customer and omnichannel needs into scalable data patterns.
• Lead data-domain ownership and governance for customer data flows.

Skills

Modular code

Reproducibility

Production-grade analytics

Digital analytics

Experimentation data

Cross-functional influence

Data governance

Education

Bachelor's in engineering, Statistics, Data Science, or Computer Sciences

Master's in Analytics or data science (preferred)

Tools

Adobe Analytics

Quantum Metrics

Job description

Academy Sports + Outdoors is seeking a senior data science leader to define and evolve reusable data, feature, and modeling patterns, as well as MLOps and production-ready analytics solutions. You will partner with CIO Data Engineering and Platform teams to influence data models, datasets, and data access standards.

The role requires translating customer and omnichannel needs into scalable patterns, enabling data scientists, analysts, and engineers to adopt standards and accelerate delivery.