Data Scientist, Employee Experience & Productivity

Apple • Sunnyvale, CA

11h

About The Position

The difference between data and intelligence is knowing what to look for and why it matters. This role is built around extracting insights that connect the two. Join Apple's Information Systems and Technology (IS&T) organization, the engine powering Apple. As an Insights Lead on the Employee Productivity & Support (EPS) Data Science team, you will serve as the dedicated data strategist for IS&T Product, which manages a portfolio of internal tools and platforms that Apple employees use every day. Success here is measured holistically — not tool by tool — and your job is to ensure data is defining what that looks like at the portfolio level, identifying where employees are well served and where they are not, and surfacing the insights that help leaders invest in the right places. This is not a role where you build dashboards and hand them off. You will work closely with leadership, understand the experience they are trying to create, mine existing and new data sources for the answers they need, and carry that business context back to the broader data science team so every asset we build stays connected to what matters most. In this role, you will be the connective tissue between IS&T's Product group and EPS Data Science. The Product group operates with a holistic view of the employee experience — where individual tools and platforms are means to an end, and success is measured by the productivity they collectively enable. You will attend leadership meetings, absorb the strategic direction, and identify where data can accelerate product decisions or illuminate blind spots. Day to day, you will move fluidly between reviewing the team's existing product dashboards, conducting deep-dive analyses on portfolio utilization, feature adoption, and employee experience patterns, building new artifacts (queries, slides, one-off analyses), and presenting findings to stakeholders who range from front-line managers to executive leadership. You will also help manage the analytical relationship for the Product group — prioritizing requests, sequencing work, and ensuring the data science team understands the evolving needs of the business. The ideal candidate combines the quantitative rigor of a strong data scientist with the strategic instincts and communication skills of a business consultant.

Requirements

• Bachelor's degree and 3 years of relevant experience in data analytics, business intelligence, data science, or a related quantitative field, or equivalent experience.
• 3+ years experience in SQL for modeling and analyzing data from large, multi-source datasets.
• 2+ years experience in data visualization tools such as Tableau, Looker, or equivalent building and interpreting analytical views.
• 2+ years experience partnering with senior product leaders to translate business problems into analytical questions, conduct analyses, and deliver data-informed recommendations that guide decisions.
• Proficiency in statistical analysis and quantitative reasoning, including descriptive statistics, hypothesis testing, and foundational causal inference methods.
• Demonstrated experience with portfolio-level product analytics — measuring utilization, adoption, and value delivery across a suite of tools or products.
• Experience collaborating across teams with partners who have varying levels of data fluency.
• Exceptional written and verbal communication skills, with comfort adapting your message for both technical and non-technical audiences.
• Comfort with ambiguity; ability to define the analytical approach when the business question is loosely framed.
• Strong interpersonal skills and the ability to build trust with leaders across diverse functional areas.

Nice To Haves

• Master's degree or PhD in a quantitative or business field (e.g., MBA with analytics concentration, statistics, data science, economics, operations research, applied mathematics, or the natural sciences)
• Familiarity with product analytics platforms, A/B testing frameworks, clickstream data, and/or feature flagging systems.
• Experience working with product management processes and how data informs roadmap prioritization, investment decisions, and portfolio rationalization.
• Experience serving as a liaison or \"translator\" between technical teams and business teams, helping manage competing priorities and maintain alignment.
• Familiarity with program or project management practices — comfortable sequencing work, managing stakeholder expectations, and tracking deliverables across teams.
• Proficiency in Python or R for exploratory analysis or scripting.
• A track record of going beyond what was asked — proactively surfacing insights that stakeholders did not know they needed.
• Experience with Gen AI tools & LLM.

Responsibilities

• Serve as the dedicated data strategist for IS&T's Product group — the right-hand person for data across Apple's portfolio of internal productivity tools, platforms, and web properties.
• Maintain deep awareness of the group's strategic direction and use that context to guide what gets measured, analyzed, and surfaced.
• Analyze operational metrics across the product portfolio — adoption rates, feature use, and engagement trends — identifying which tools are delivering value, where the portfolio can be rationalized, and where further investment is warranted.
• Extract and deliver user insights that deepen leadership's understanding of the employee experience holistically — how employees accomplish tasks across the tool ecosystem, where friction exists, what adoption journeys look like, and where tools overlap or leave gaps.
• Measure the impact and effectiveness of product strategy decisions, launches, and experience changes, connecting actions to outcomes and helping leaders understand whether the overall direction is working — not just whether an individual feature shipped.
• Help establish consistent measurement frameworks across the product portfolio, so that success is defined and tracked the same way regardless of the tool — enabling meaningful comparison and prioritization across the ecosystem.
• Conduct targeted deep-dive analyses when existing dashboards and reports do not have the answer — writing SQL, building visualizations, conducting in-depth analyses, and packaging findings into clear, audience-ready deliverables.
• Bring business context, strategic shifts, and evolving analytical needs back to the data science team on a regular basis, ensuring the team stays connected to the \"why\" behind the work and that new assets are built with the right priorities in mind.
• Help prioritize and manage the flow of analytical requests from Product leadership, balancing urgency, impact, and feasibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior