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Sr Manager Applied Intelligence

Job in Katy, Harris County, Texas, 77494, USA
Listing for: Academy Sports + Outdoors
Full Time position
Listed on 2026-10-17
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer (Applied/Software), Data Science Manager, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 190000 USD Yearly USD 150000.00 190000.00 YEAR
Job Description & How to Apply Below
Who We Are

At Academy Sports + Outdoors our vision is to be the best sports + outdoors retailer in the country — but what truly sets us apart is our people. We’re a passionate, purpose-driven team that’s as committed to each other as we are to our customers.

We’ve spent over 80 years building a culture that puts people first. We believe in creating opportunities for growth, fostering meaningful connections, and supporting every Team Member’s journey. What fuels us? Our belief in the power of fun.

Here, you won’t just help customers gear up for their next adventure — you’ll launch one of your own. Whether you're starting out or leveling up, Academy is a place where fun can’t lose!

What You Will Work On

In this role, you shape scalable, reusable, production-grade data science and artificial intelligence capabilities that support customer, marketing, and omnichannel work. Your leadership helps teams move faster with shared data, feature, modeling, MLOps, and model-lifecycle patterns instead of rebuilding solutions for each need. By embedding quality, fairness, trust, compliance, and practical governance into the work, you help create analytics and machine learning solutions that can be used safely and effectively at scale.

Working across the customer data domain, you translate business needs into technical patterns aligned with enterprise platforms and standards. You influence priorities through evidence, design proposals, and proof-of-value work while enabling data scientists, analysts, and engineers to adopt common approaches and reduce reinvention. Your scope also includes leading Adobe Analytics and Quantum Metrics data capture, governing customer-facing data domains such as tag management, Bridg, and clean room capabilities, and helping define secure, documented customer data flows.

Who

You Will Work With

You will partner with CIO, Data Products, Engineering, AI COE, IT pod, platform, and governance teams to influence customer data models, shared datasets, feature reuse, data access, and consumption standards. These partnerships connect customer-domain needs with secure, scalable technical foundations and practical governance for personalization, experimentation, and customer analytics.

Across a matrixed organization, you will support domain-aligned data scientists, analysts, and engineers while building trust with both business and technical stakeholders. The work calls for clear standards, evidence-based influence, and the confidence to let teams execute independently while keeping quality, reuse, and downstream usability in focus.

What You Bring

Bring your energy, your ideas, and your love for sports and the outdoors.

  • 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, applied machine learning, or related fields, with retail or B2C preferred
  • 4+ years leading teams or major technical initiatives, including people management or matrixed leadership
  • 3+ years in B2C, retail, e-commerce, marketing analytics, or customer-facing analytics domains
  • 3+ years building, deploying, or enabling production-grade analytics or ML solutions
  • Strong engineering mindset with modular code, reproducibility, and production-grade analytics or ML systems
  • Background working with digital analytics, customer data platforms, or experimentation data such as Adobe, web or app analytics, or similar ecosystems
  • Proven ability to influence across matrixed organizations without direct ownership
  • Background partnering with data engineering, platform, and governance teams
  • Ability to balance speed to value with long-term scalability
  • MLOps or analytics platform enablement preferred
  • Exposure to customer analytics,…
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