The people here at Apple don’t just build products — we craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that supports the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work. Join Apple, and help us leave the world better than we found it!

Retail Engagement & Marketing (REM) is a diverse and multi-disciplinary organization. We are marketers, strategists, creatives, producers and program managers whose role it is to help Apple Retail care for our customers and elevate our teams. We build insights, experiences and programs all in service of bringing together the very best of Apple to help us reach more people, grow our business, and enrich lives.

We are looking for someone with deep expertise in analytics and a proven track-record as a people leader. Lead the analytics needs of Retail Engagement Marketing, helping to define a performance framework across campaigns, programs and platforms both online and in store.

Imagine what you will do here!

Lead a small team who will work cross functionally to define problem statements, define requirements and develop briefs. You’ll also be responsible for QBR program management, prep for leadership reviews and support strategic decisions. Collaborate with other analytic functions to pipeline, generate and present data and insights.

RESPONSIBILITIES INCLUDE:
Cross-functional data reporting: Partner with Analytics functions across the business to pipeline, generate and stitch together data and insights. Build the management system to ensure real-time, accurate information, from data intake, mining, engineering, validation, as well as modeling, dashboard visualization and communications.

Request Intake: Manage cross functional partners on all aspects of data/reporting needs, partnering to fully understand business needs and priorities. Ensure briefs are clear and ladder back into strategic priorities, translating business needs into analytic requirements. Oversee the end to end process, prioritizing and tracking requires across multiple stakeholders.

Quality Control: Develop and implement quality controls and departmental standards to ensure consistency, organizational expectations and regulatory requirements.

Data-Driven Insights: Utilize data analytics and reporting tools to derive actionable insights, measure performance, and inform decision-making processes. Connect marketing, programming and commercial data for team and customers through data visualizations.

Drive Decision-Making Excellence: Develop and implement a comprehensive decision-making framework that fosters collaboration, critical thinking, and data-driven decision-making across the organization.

Process Improvement: Identify and implement process improvements to streamline workflows, reduce redundancies, and enhance operational efficiency in data collection and decision making.

Team Leadership: Lead and mentor direct reports supporting them through their career journey and development at Apple. Promote a culture of continuous learning and development, fostering an innovative and adaptable team. Role model inclusive leadership behaviors and build, develop and retain diverse teams.

Stakeholder Engagement: Collaborate with leadership, cross-functional teams and external stakeholders to understand business needs, align initiatives and drive adoption.

AI Innovations: stay current with future proofs technologies, and partner across Apple to leverage the automation / AI solutions to arrive at the very best of insights to drive business decisions.

Performance Management: Implement effective performance management systems to assess and develop talent, drive accountability, and achieve organizational goals.

5+ years of experience in a position monitoring, managing, manipulating and drawing insights from data3+ years of experience leading a teamProficient in data visualization tools: Tableau, Raw, chart.js, etc.Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources.Strong SQL skills, ability to perform effective querying involving multiple tables and sub-queries.Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.Bachelor degree in Data Intelligence or equivalent and relevant work experience