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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.","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
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
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
Pay & Benefits
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 $133,500 and $246,200, 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.