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The 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.
Description
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.
Responsibilities
Define business requirements and prediction objectives that guide ML model development - translating domain estimation logic into clear data inputs, target outputs, and accuracy expectations Identify and map upstream data sources that serve as trigger signals for Capex prediction, documenting the pipeline requirements needed to feed the predictive framework Partner with the ML engineering team and X-functional partners as domain expert and product owner, providing the manufacturing and Capex context to ML Engineering team. Build and maintain the requirements framework for how predictive capabilities are extended as real-time design guidance tools for cross-functional partners Strengthen and scale the team's role in design guidance -- transforming existing estimation practices into a predictive intelligence capability that delivers greater precision and earlier insight into capital impact Communicate model outputs, capabilities, and limitations clearly to both technical teams and non-technical executive and operational audiences Continuously expand your technical depth and domain understanding to strengthen the quality of the requirements and context you bring to the ML partnership Approximately 15% international travel
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
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $128,400 and $193,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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
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Apple accepts applications to this posting on an ongoing basis.