Data Analyst I, Analytics Reporting
K
Khan AcademyEducation, Non-profit
Continental US + Hawaii + Canada OnlyTemporaryEntry
Salary107712 - 163746 USD per year
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Job Details
- Experience
- At least 2 years
- Required Skills
- SQLMicrosoft Power BITableauLooker
Requirements
- At least 2 years of experience in analytics, business intelligence, or a related role (internships/academic projects welcome)
- Solid SQL skills (comfortable querying, joining tables, and validating results)
- Experience building dashboards and visualizations in a BI tool (e.g., Looker, Tableau, Power BI)
- Interest in or experience with AI tools (e.g., LLMs) and a willingness to learn how to build and iterate on AI-driven solutions
- Comfort working with spreadsheets and slide decks to present metrics clearly and consistently
- Strong attention to detail and a healthy skepticism: you like validating numbers before sharing them widely
- Clear communication skills, especially with non-technical stakeholders, and the ability to explain definitions and caveats
- Ability to manage multiple requests, prioritize effectively, and meet deadlines for recurring reporting cycles
- Proven cross-cultural competency skills demonstrating self-awareness, awareness of other, and the ability to adopt inclusive perspectives, attitudes, and behaviors
- Familiarity with Python or R is a plus
- Prior experience in education, nonprofits, or funder-facing reporting is a plus
Responsibilities
- Produce recurring reporting for senior leadership, including maintaining and updating Monthly Business Review (MBR) slides with company-level KPIs and narrative context
- Build, own, and continuously improve self-serve dashboards for organizations/teams (e.g., Philanthropy and cross-functional leaders), ensuring metrics are clearly defined, quality checked for data issues, well-documented, and trusted
- Respond to reporting requests from Philanthropy (including funder reporting), translating questions into clear requirements, pulling the right data, and delivering outputs on schedule
- Align on metric definitions, reconcile discrepancies, and partner with data/engineering where instrumentation or pipeline issues impact reporting
- Create lightweight analyses to add context to reporting (segmentation, comparisons over time, funnel summaries), and communicate findings in plain language
- Improve reporting workflows by templating, documenting processes, and automating repeatable tasks, while shifting toward building AI-powered, self-serve access via AI agents
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