Institutional Data Analyst
At a glance
Mid-level Data Analysis & BI role at Weill Cornell Medical College. New York · $83,400–$94,800 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build standard and one-off reports with advanced DAX features, drill-through views and custom layouts
- Use fund and general-ledger data to support forecasting, reporting and institutional performance tracking
- Turn finance, academic and operational questions into validated reporting requirements and useful analyses
- Create and maintain Power BI or Tableau dashboards, then improve existing workflows through automation and usability changes
- Clean and combine data with SQL and Python, document solutions, support users and prepare survey submissions
What you bring
- A bachelor’s degree in math, statistics, computer science or another related technical field
- Around three to five years as a data analyst, including professional Python work and Power BI or Tableau modeling and visualization
- Experience customizing metrics with DAX and VizQL, and analyzing data from SQL warehouses, BI marts or another listed source
- You can frame analysis questions, test hypotheses and use the findings to produce measurable business impact
Who this fits
This role suits a data analyst who can work across finance, academic and operational reporting and manage several priorities at once. It is based in Midtown, New York, and calls for collaboration with stakeholders across teams.
From the employer
Title: Institutional Data Analyst
Location: Midtown
Org Unit: Institutional Reporting
Work Days:
Weekly Hours: 35.00
Exemption Status: Exempt
Salary Range: $83,400.00 - $94,800.00
*As required under NYC Human Rights Law Int 1208-2018 - Salary range for this role when Hired for NYC Offices
Position Summary
The Institutional Data Analyst develops and delivers data-driven insights that support strategic decision-making across the organization. This role is responsible for designing, building, and maintaining reporting solutions, ensuring data accuracy, and translating complex information into meaningful analyses aligned with institutional goals. The analyst works closely with stakeholders across finance, academic, and operational areas.
Job Responsibilities
- Create complex standard and ad hoc reports using advanced techniques (e.g., DAX, drill-through functionality, and custom layouts) to meet diverse business needs.
- Develop expertise and apply knowledge of higher education fund and general ledger data to support reporting, forecasting, and institutional performance tracking.
- Apply knowledge of institutional operations - including budgeting, research, clinical, academic, and education functions – to deliver relevant and insightful analyses.
- Collaborate with stakeholders to gather, document, and validate reporting requirements, translating business needs into actionable data solutions.
- Design, develop, and maintain reporting infrastructure, dashboards, and visualizations using BI tools such as Power BI and Tableau to support institutional decision-making.
- Maintain and enhance existing reporting workflows, identifying opportunities for automation, efficiency, and improved usability.
- Integrate, clean, and transform data from multiple sources using tools such as SQL and Python ensuring accuracy, consistency, and optimal performance.
- Produce clear technical documentation and provide end-user support, while managing multiple priorities and collaborating across teams to deliver high-quality outcomes.
- Participate in institutional data collection, review, analysis, and submission of reports for various surveys, including IPEDS, AAMC, LCME, and more.
- Perform other related duties as assigned.
Education
- Bachelor’s degree in math, statistics, computer science or related technical field.
Experience
- Budget subject matter experience preferred
- Approximately 3-5 years’ experience as a Data Analyst with direct professional experience with Python (Pandas, Numpy, similar libraries), modeling and visualization with Power BI and Tableau, metrics customization with DAX and VizQL
- Experience accessing, cleansing and performing analysis from one or more of the following sources: transactional tables, OLAP data models, BI data marts, SQL-based data warehouses, semi-structured/unstructured data environments
- Experience outlining objectives, forming hypotheses, and carrying out analysis to drive measurable business impact
Knowledge, Skills and Abilities
- Demonstrated implementation of critical thinking, initiative, and ability to manage multiple responsibilities in a fast-paced work environment.
- Ability to adjust and adapt to satisfy multiple priorities.
Licenses and Certifications
Working Conditions/Physical Demands
Cornell welcomes students, faculty, and staff with diverse backgrounds from across the globe to pursue world-class education and career opportunities, to further the founding principle of “any person, any study.” No person shall be denied employment on the basis of any legally protected status or subjected to prohibited discrimination involving, but not limited to, such factors as race, ethnic or national origin, citizenship and immigration status, color, sex, pregnancy or pregnancy-related conditions, age, creed, religion, arrest and/or conviction record, military or veteran status, sexual orientation, gender expression and/or identity, an individual’s genetic information, domestic violence victim status, familial status, marital status, or any other characteristic protected by applicable federal, state, or local law.
Cornell University embraces diversity in its workforce and seeks job candidates who will contribute to a climate that supports students, faculty, and staff of all identities and backgrounds. We hire based on merit, and encourage people from historically underrepresented and/or marginalized identities to apply. Consistent with federal law, Cornell engages in affirmative action in employment for qualified protected veterans as defined in the Vietnam Era Veterans’ Readjustment Assistance Act (VEVRRA). We also recognize a lawful preference in employment practices for Native Americans living on or near Indian reservations in accordance with applicable law.
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