CapEx Data Optimization Product Manager

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don't just create products - they create the kind of wonder that has revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it.

The Product Operations Data Team is looking for an analytically sharp, intellectually curious individual to own the data optimization vision for our Capex Equipment Engineering organization. This is not a model-building role - it is an architectural and strategic one. You will serve as the critical bridge between deep Capex domain knowledge and the technical capabilities of a dedicated ML engineering team, translating what the business needs to predict into what the models need to learn. This is a high-growth opportunity for a driven, curious individual who is ready to own something significant and expand their impact as the vision scales.

Description

In this role you will define, shape, and drive the data optimization frameworks that transform how the Capex team operates - shifting from manual estimation to model-driven prediction that influences product design decisions before commitments are made.

Minimum Qualifications

3+ years of experience in an analytical, data, or technically oriented role

BS or MS degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent hands-on experience

Strong quantitative analytical skills - comfortable working with complex, multi-source datasets to extract meaningful signals

Foundational understanding of how predictive models work - what they require as inputs, how they are trained, and how their outputs should be interpreted and validated

Demonstrated ability to translate ambiguous business problems into structured, precise requirements that a technical team can act on

Preferred Qualifications

5+ years of experience in an analytically driven role with increasing scope and ownership

Some exposure to manufacturing, supply chain, or capital equipment environments - enough to engage credibly with domain concepts and recognize when a model output makes operational sense

Experience working at the interface between business and engineering teams, serving as a translator or connector across functions

Familiarity with data pipeline concepts, feature engineering, and model validation practices - even without hands-on model building experience

Experience defining requirements for ML or data products and partnering with technical teams through the development lifecycle

Clear and confident communicator, able to represent team needs to a technical audience and explain complex analytical concepts to non-technical stakeholders

Demonstrated intellectual curiosity and a track record of growing technical depth independently in a fast-moving environment

Comfortable operating in ambiguous, early-stage problem spaces where the framework itself is still being defined