AI Data Intelligence Leader WW Channel Sales

AI Data Intelligence Leader — WW Channel Sales

May 14, 2026

40 Weekly Hours

Role Number: 200630419

Apple's WW Channel Sales & Operations organization builds AI systems that predict optimal coverage, run experiments autonomously, and deliver decision intelligence across all global sales programs. In an increasingly agentic world, these models don't just inform human decisions — they power autonomous agents that act on them at global scale. This role owns the product vision and ML strategy for the decision intelligence platform that enables both people and agents to make better decisions, faster.

Description

You will own CSO's decision intelligence platform end-to-end: defining what it should do, building the ML models that power it, and scaling it globally. This spans predictive coverage models, an experimentation and uplift engine, a unified data management system across all sales programs, and the real-time visibility layer that surfaces automated insights to program leaders. The primary consumers of your models and intelligence layer are AI agents that make autonomous decisions. This changes what data quality means, what latency is acceptable, and how systems need to be designed. You'll lead a team of data scientists while partnering with a separate data engineering team for pipeline and infrastructure work, and a separate full-stack development team for product surfaces — though increasingly, agents will handle much of the integration and delivery work themselves.

Responsibilities

• Own the product vision and roadmap for CSO's decision intelligence platform — spanning predictive coverage, experimentation & uplift, anomaly detection, and proactive automated insights
• Define the ML model portfolio: predictive coverage (live and scaling globally), staffing optimization, causal uplift estimation, and anomaly detection — from prototype through production
• Define the framework for model and agent autonomy: which decisions they make independently, which they recommend, and how human feedback loops improve quality over time
• Define the requirements, contracts, and quality standards for the unified data management system — a structured data foundation spanning all global sales programs that serves both ML models and human decision-makers
• Partner with the dedicated data engineering team to design and prioritize data pipelines that serve real-time decision loops and batch analytical workloads, with clear contracts for freshness, completeness, and provenance
• Establish data quality as a safety concern — when models and agents act autonomously on data, bad data produces wrong decisions at scale. Define observability, lineage, and automated drift detection requirements for the data engineering team to implement
• Build the global experiments library and design workflow — enabling program teams to run A/B tests, measure causal uplift, and make investment decisions based on evidence
• Establish measurement frameworks for model quality: accuracy, calibration, false positive rates, and the rate at which human overrides indicate improvement opportunities
• Lead a team of data scientists — building the culture and capability to ship ML- powered decision products at Apple's quality bar
• Partner with the data engineering team to translate model requirements into pipeline priorities, data contracts, and quality SLAs — you define what data is needed and to what standard; they build and operate the pipelines
• Partner with the full-stack development team when product surfaces are needed — dashboards, interactive tools, or user-facing features that go beyond what agents deliver autonomously
• Drive quarterly data prioritization with program owners — maintaining a minimalist, high-integrity data architecture that is technology-agnostic and systematically updatable
• Partner with GEO teams to scale capabilities globally, and with cross-functional partners (Finance, Product Marketing, IS&T, AVA Platform) to integrate with Apple's broader technology ecosystem

Minimum Qualifications

• 15+ years in data science, ML, or AI product leadership, with 5+ years managing technical teams
• Experience owning ML model portfolios in production — predictive models, experimentation systems, or decision intelligence products with measurable business outcomes
• Strong understanding of production data systems (Spark, Databricks, Kafka, Airflow, Snowflake, or equivalent) — sufficient to define requirements, set quality contracts, and partner effectively with a data engineering team
• Strong fluency in SQL, Python, and cloud data platforms (GCP/AWS)
• Understanding of how AI agents and LLMs consume data: retrieval patterns, context engineering, freshness requirements, and quality guarantees needed for autonomous decision making
• Track record of treating data quality as a product feature, not a cleanup task
• Proven ability to lead through influence across teams you don't directly manage — especially data engineering and product development teams
• Proven ability to translate between technical teams and senior leadership — making complex AI and data concepts concrete and decision-relevant
• BS/MS in Computer Science, Data Engineering, or related discipline

Preferred Qualifications

• Experience with predictive analytics in retail, channel, or field operations — coverage models, staffing optimization, or demand forecasting
• Background in causal inference, experimentation platforms, or uplift modeling
• Experience building or leading agentic AI systems in production
• Experience scaling ML products globally across multiple markets with varying data availability
• Understanding of data privacy and governance in contexts where AI systems autonomously access and act on business data
• A design-minded sensibility — valuing simplicity, trust, and user empathy as much as model performance

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple's workplace Learn about reasonable accommodations for job applicants Apple accepts applications to this posting on an ongoing basis. Submit Resume Back to search results See all roles in Austin