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Senior Data Science Manager - Worldwide Product Marketing

Yesterday Cupertino, CA

As a Senior Data Science Manager, you will lead and grow a high-performing team of data scientists driving analytics, experimentation, modeling, and data-driven insights that shape business strategy and product experiences. Operating at both the strategic and execution levels, you will set the team's analytical vision and roadmap while staying close enough to the work to guide modeling, machine learning, and production readiness. As a trusted advisor to leadership, you will bring clarity to complex problems and influence decisions with evidence-based recommendations.

Description

• Lead data science initiatives end-to-end-from scoping and data prep to modeling, visualization, and delivery

• Provide technical direction and review analytical approaches, ML models, and dashboards

• Set standards for code and data quality, reproducibility, and production readiness, partnering with Engineering and ML teams on scalable solutions

• Champion the responsible use of LLMs and AI-assisted tooling to accelerate insights, visualization, and modeling

• Set the analytical vision and multi-quarter roadmap, aligned to business priorities and Apple's broader goals

• Prioritize competing initiatives, balancing quick wins against long-term platform and capability investments

• Anticipate where the discipline is heading-including AI/LLM and agentic workflows-and shape the team's capabilities accordingly

• Translate business questions into analytical frameworks, and analytical results into actionable decisions

• Serve as the primary thought partner for Finance, Marketing, Engineering, Product, and cross-functional stakeholders

Preferred Qualifications

Strong foundation in statistics, experimentation design, causal inference, and ML methodologies

Proficiency in SQL and Python

Experience with large, complex datasets, data pipelines, and production-level analytics systems

Proven ability to drive measurable business impact through data and automation

Exceptional communication skills, able to influence technical and non-technical stakeholders

Ability to operate effectively in ambiguous, complex environments and set clear direction

Minimum Qualifications

10+ years of experience in data science, analytics, or applied machine learning

2+ years leading, mentoring, and scaling data-focused teams

Bachelor's degree in Computer Science, Statistics, Applied Math, Engineering, or a related field

Pay & Benefits

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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 $212,600 and $319,800, 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.

Client-provided location(s): Cupertino, CA
Job ID: apple-200671821-0836
Employment Type: OTHER
Posted: 2026-07-24T20:06:46

Perks and Benefits

  • Health and Wellness

    • Parental Benefits

      • Work Flexibility

        • Office Life and Perks

          • Vacation and Time Off

            • Financial and Retirement

              • Professional Development

                • Diversity and Inclusion

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