What You Will Work OnIn 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 WithYou 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 BringBring 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, personalization, marketing, or e-commerce use cases preferred
- Background operating in early-to-mid maturity data organizations preferred
- Comfort shaping standards without formal authority preferred
- A team-first attitude; while your core duties are your priority, you're happy to step in wherever you're needed
Work Style and Physical Requirements- Systems-thinking approach with a pragmatic bias toward delivery
- Ability to build trust with business and technical stakeholders
- Comfort enabling teams to execute independently while influencing across a matrixed organization
- Focus on scale and reuse rather than personal ownership
- Regular in-office attendance is required
- Acceptable level of hearing and vision to perform job duties
- Ability to adhere to company policies and professional standards
Key SkillsTechnology Enablement, Data Collection Management, Quality Assurance and Control, Influencing Others, Process Building, Security
