Data Science Manager - System Analytics & Intelligence

Summary

Core OS ships the foundational software that powers every Apple product. At the scale and complexity of that work, accelerating developer productivity, elevating software quality, and shaping where the organization invests next demands more than intuition. It requires turning massive amounts of workflow data into clear, strategic intelligence. The System Analytics & Intelligence (SAIL) team exists to do exactly that: identify what matters most, drive meaningful improvements to the developer experience, and help drive the initiatives that keep Core OS teams focused on highest-impact work.

We are looking for a leader who is passionate about that problem, someone who sees data not as an end in itself, but as a means to drive real organizational change. You will lead a team of data scientists and analysts, and you will define what it means for Core OS to truly understand itself: to see the forest, not just the trees, and to point confidently to where investment will have the greatest impact on quality and developer productivity.

Description

As the manager for the SAIL team, you will own the vision and execution for how Core OS measures what matters and acts on it. The opportunity ahead is to build the strategic intelligence function for Core OS: systems that synthesize signals from across the development lifecycle to proactively identify systemic bottlenecks, predict quality risk, and guide leadership investment decisions before problems escalate.

This role requires more than technical depth in data engineering and analytics. It requires the judgment to know which questions are worth asking and the influence to ensure the answers drive action. You will build and maintain strong partnerships with engineering teams, workflow champions, and leadership across Core OS organizations. Candidates who thrive in this role will be energized by ambiguity, motivated by impact, and committed to building something Core OS didn't know it needed.

Responsibilities

Manage, mentor, and grow a team of data scientists and analysts; coach team members to connect their work to measurable outcomes and gradually build a culture where the team drives impact, not just delivery

Define and execute the technical vision for Core OS workflow analytics, guiding the design and development of large-scale data pipelines, transformation workflows, and analytics platforms

Move the team beyond reporting and toward proactive strategic intelligence, synthesizing signals across Core OS to surface investment recommendations and identify systemic quality and productivity risks before they escalate

Partner with stakeholders across Core OS organizations to identify analytics needs, prioritize initiatives, and drive adoption of data products that improve developer productivity and software quality

Lead efforts to apply emerging technologies like LLMs, graph-based diagnostics, and predictive analytics to Core OS workflow and quality problems

Minimum Qualifications

5+ years of experience building production data systems (Python, SQL, or similar languages) and working with data platforms and distributed systems

Strong foundation in data analytics, including experience with business intelligence tools, statistical analysis, and data visualization

Demonstrated ability to translate complex data into actionable insights and clear narratives for technical and executive audiences

Excellent stakeholder management skills with experience partnering across multiple teams and organizations

Proven track record of delivering data products that drive measurable business or engineering outcomes

Preferred Qualifications

5+ years of experience leading teams of data engineers, data scientists, or analytics engineers

Experience with modern data stack tools, business intelligence platforms such as Tableau, and background in software development workflows, CI/CD systems, or developer productivity

Experience with graph databases, graph algorithms, or machine learning/LLM applications in software engineering domains

Experience making data insights easily accessible to stakeholders through web services, APIs, or other scalable delivery mechanisms across large engineering organizations

Advanced degree in Computer Science, Data Science, Statistics, or related field

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