Job 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. 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 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

Requirements

Must-haves

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
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

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

Platform: apple
Effort: medium