Support Operations Data Analyst, Employee Experience & Productivity, IS&T - Jobs - Careers at Apple
- Partner with support leaders and operational managers to understand their needs, translate business questions into data problems, and deliver recommendations grounded in evidence.
- Extract, clean, transform, and validate data from multiple support systems — including ticketing platforms, contact center tools, and AI interaction logs — creating reliable datasets for analysis and visualization.
- Build and maintain dashboards and reports in Tableau, and actively consume those assets to identify trends, surface anomalies, and communicate insights back to stakeholders.
- Conduct deep-dive analyses on support operations data to answer questions that existing dashboards do not address — packaging findings into clear, audience-ready deliverables such as slides or annotated visualizations.
- Use AI to accelerate insight generation — summarizing patterns, classifying data, and enhancing the speed and depth of analytical work — while validating outputs to ensure accuracy and reliability.
- Develop and maintain well-documented, reproducible analytical workflows — writing clean SQL, organizing code in GitHub, and ensuring that analyses can be understood and extended by others on the team.
- Monitor data quality across support data sources, flagging issues proactively and working with data engineering to resolve them.
- 3+ years of experience working with IT support data, including ticketing systems, contact center platforms, or multi-channel interaction data.
- 3+ years of hands-on experience writing SQL to extract, transform, and analyze data from large, multi-source datasets.
- 3+ years of experience building dashboards and visualizations in Tableau, Looker, or equivalent.
- 1+ years of experience in Python or R for data manipulation and analysis.
- 3+ years of experience delivering analytical work in a fast-paced environment with evolving priorities and multiple concurrent stakeholders.
- Bachelor's degree and 3+ years of relevant experience in data analytics, business intelligence, data science, or a related quantitative field — or a Master's degree in a quantitative or business discipline with 2+ years of relevant experience.
- Master's degree or PhD in a quantitative or business field (e.g., statistics, data science, economics, operations research, applied mathematics, the natural sciences, or an MBA with analytics concentration)
- Working knowledge of support operations and how data informs staffing models, triage optimization, and process improvement.
- Working knowledge of clickstream data and web analytics as applied to content or service performance measurement.
- Proficiency in version control and collaborative documentation practices using tools like GitHub.
- Knowledge of statistical modeling, including hypothesis testing, regression, and foundational causal inference methods.
- Track record of applying AI to real-world data analytics and general productivity challenges.
- Ability to communicate analytical findings clearly to both technical and non-technical audiences, adapting depth and format to the situation.
- Comfort with ambiguity; ability to define the analytical approach when the business question is loosely framed.
- Proven ability to build trust with leaders across diverse functional areas.
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Required Skills
Required Languages
🇬🇧 English