Capex Predictive Intelligence 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 theres no telling what you could accomplish. The people here at Apple dont just create products - they create the kind of wonder that has revolutionized entire industries. Its 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 Product Operations Data Team is looking for an analytically sharp intellectually curious individual to own the predictive intelligence 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.n

In this role you will define shape and drive the predictive intelligence framework that transforms how the Capex team operates - shifting from manual estimation to model-driven prediction that influences product design decisions before commitments are made.

Define business requirements and prediction objectives that guide ML model development - translating domain estimation logic into clear data inputs target outputs and accuracy expectationsnIdentify and map upstream data sources that serve as trigger signals for Capex prediction documenting the pipeline requirements needed to feed the predictive frameworknPartner with the ML engineering team and X-functional partners as domain expert and product owner providing the manufacturing and Capex context to ML Engineering and maintain the requirements framework for how predictive capabilities are extended as real-time design guidance tools for cross-functional partnersnStrengthen and scale the teams role in design guidance -- transforming existing estimation practices into a predictive intelligence capability that delivers greater precision and earlier insight into capital impactnCommunicate model outputs capabilities and limitations clearly to both technical teams and non-technical executive and operational audiencesnContinuously expand your technical depth and domain understanding to strengthen the quality of the requirements and context you bring to the ML partnershipnApproximately 15% international traveln

3 years of experience in an analytical data or technically oriented rolenBS or MS degree in Computer Science Engineering Data Science or a related quantitative field or equivalent hands-on experiencenStrong quantitative analytical skills - comfortable working with complex multi-source datasets to extract meaningful signalsnFoundational understanding of how predictive models work - what they require as inputs how they are trained and how their outputs should be interpreted and validatednDemonstrated ability to translate ambiguous business problems into structured precise requirements that a technical team can act onn

5 years of experience in an analytically driven role with increasing scope and ownershipnSome exposure to manufacturing supply chain or capital equipment environments - enough to engage credibly with domain concepts and recognize when a model output makes operational sensenExperience working at the interface between business and engineering teams serving as a translator or connector across functionsnFamiliarity with data pipeline concepts feature engineering and model validation practices - even without hands-on model building experiencenExperience defining requirements for ML or data products and partnering with technical teams through the development lifecyclenClear and confident communicator able to represent team needs to a technical audience and explain complex analytical concepts to non-technical stakeholdersnDemonstrated intellectual curiosity and a track record of growing technical depth independently in a fast-moving environmentnComfortable operating in ambiguous early-stage problem spaces where the framework itself is still being definedn