Role Overview:
The Data Analyst will be a foundational member of our AI initiative, focused on leveraging
and optimizing the AI and analytics capabilities embedded within our key technology
platforms, including EPIC and Workday. This role will be more about investigating complex
business questions, extracting, cleaning, preparing data for advanced analytics, and
ensuring the quality of our data assets. The ideal candidate is a curious problem-solver
with a strong grasp of data exploration and a passion for finding insights that can drive our
AI initiatives.

Key Responsibilities:
• Collaborate with Data Scientists and business stakeholders to understand complex
business problems and translate them into actionable data analysis tasks.
• Perform deep-dive, exploratory data analysis to uncover trends, identify data quality
issues, and validate assumptions related to our EPIC and Workday systems.
• Work closely with the Data Engineer to define data requirements for building robust
pipelines that support our analytical and AI needs.
• Monitor the performance of vendor-provided AI capabilities within EPIC and
Workday, using data to identify discrepancies and opportunities for optimization.
• Contribute to the design and development of data models that are fit for purpose,
both for human analysis and for machine learning models.
• Create ad-hoc visualizations and presentations to communicate complex findings
and insights to technical and non-technical audiences.
• Assist in documenting data sources, business logic, and analysis methodologies.

Required Skills & Qualification:
• SQL: Strong proficiency in SQL for complex data manipulation, aggregation, and
analysis.
• Data Exploration & Analysis: Proven ability to use data to investigate business
problems and validate hypotheses. Experience with data profiling, cleansing, and
validation.
• Problem-Solving: Proven ability to break down complex business problems into
solvable data-driven questions and find creative solutions.
• Communication: Excellent verbal and written communication skills with the ability
to explain complex data concepts and findings clearly.
• Education: Bachelor's degree in a quantitative field such as Computer Science,
Statistics, Mathematics, Economics, or a related discipline.
• Domain Knowledge: Previous experience working with or analyzing data from
major enterprise systems like EPIC (e.g., Epic Clarity) or Workday.

Nice-to-Have Skills:
• Cloud Platforms: Familiarity with cloud data services (preferably Azure but other
cloud experiences are good too).
• Data Visualization Tools: While not a primary focus, some experience with BI tools
like Power BI or Qlik is a plus for creating ad-hoc visualizations.
• Understanding of AI/ML Concepts: A foundational understanding of machine
learning models and the data required to build and evaluate them.
• Automation: Experience with or an understanding of automation platforms (e.g.,
UiPath, Power Automate) and how to analyze their impact.
• Data Modeling: Experience creating logical data models that can be physicalized
by other teams
• Feature Management: Experience documenting and managing model features