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INSPYR Solutions
Senior Manager, Data Science and AI Platform Enablement
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What they do
A Data Science Manager manages a team of data scientists, machine learning engineers and big data specialists. They lead data mining and collection procedures, ensure data quality and integrity, build analytic systems and predictive models, and test the performance of data science products.
$153,299 / year median in Texas
+25% projected growth
Job Description
Back To Results Senior Manager, Data Science and AI Platform Enablement Posted at: 08/28/2026 Onsite
- IT•AI / Data Science / Machine Learning•Direct Placement•
Job ID:
26-159065Role:
Sr Manager Data Science and AI Platform Enablement Location:
Katy, TX 77449Duration:
Direct Hire Work Authorization:
US Citizen or Green Card Holder Education :
Bachelor's in engineering, Statistics, Data Science, or Computer Sciences Master's degree in Analytics or data science (preferred)Work Experiences:
8+ years of experience in data science, advanced analytics, applied machine learning, or related fields. Experience in retail or B2C is preferred 4+ years of experience leading teams or major technical initiatives, including people management or matrixed leadership 3+ years of experience in B2C, retail, e-commerce, marketing analytics, or customer-facing analytics domains 3+ years of experience building, deploying, or enabling production-grade analytics or ML solutionsSkills:
Strong engineering mindset with experience in: Modular code, Reproducibility & Production-grade analytics or ML systems Experience working with digital analytics, customer data platforms, or experimentation data (e.g., Adobe, web/app analytics, or similar ecosystems) Proven ability to influence across matrixed organizations without direct ownership Experience partnering with data engineering, platform, and governance teams Ability to balance speed to value with long-term scalability Experience enabling MLOps or analytics platforms, preferred Exposure to customer analytics, personalization, marketing, or e-commerce use cases, preferred Experience operating in early-to-mid maturity data organizations, preferred Comfort shaping standards without formal authority, preferredResponsibilities:
Platform & AI Standards Enablement Define and evolve reusable data, feature, and modeling patterns, MLOps and model lifecycle standards, and production-ready analytics/ML solutions. Partner with CIO Data Engineering and Platform teams to influence canonical customer data models, shared datasets, feature reuse, and data access/consumption standards. Customer Domain Translation & Enablement Translate customer, marketing, and omnichannel needs into scalable technical and platform-aligned patterns. Enable domain-aligned data scientists, analysts, and engineers to adopt standards, reduce reinvention, and accelerate delivery.- Influence enterprise priorities through evidence, design proposals, and proof-of-value work.
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