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The CUNY Office of Careers & Industry Partnerships (OCIP) is dedicated to the mission of connecting academic pursuits with career competitiveness. We build innovative educational and career development programs that strengthen and advance The City University of New York’s commitment to promoting equity and mobility for its students.  

OCIP's CUNY Internship Programs (CIP) partners with New York City agencies, boards, and commissions to provide CUNY students with internships in tech, engineering, public health, finance, business and other burgeoning sectors.  Currently, CIP is seeking a Data Analyst Intern to be placed in NYC Department of Health and Mental Hygiene (DOHMH). 
 

Responsibilities: 

  • Data Collection: Gather data from various sources, including databases, and spreadsheets.
  • Data Cleaning and Preparation: Clean, filter, and organize data to ensure accuracy and reliability for analysis.
  • Data Analysis: Utilize statistical techniques and tools to analyze large datasets and extract meaningful insights. Identify trends, patterns, and correlations in the data.
  • Data Visualization: Create and maintain interactive visualizations through data interpretations and analysis, utilizing from multiple data sources to present findings to IT Leadership and other stakeholders.
  • Reporting: Prepare and maintain reports for presentations summarizing key findings and recommendations for strategic decision-making.
  • Strategic Support: Collaborate with IT Leadership to understand business objectives and provide analytical support for strategic initiatives.
  • Continuous Improvement: Stay updated on industry trends and best practices in data analysis and contribute to the improvement of data processes and methodologies. 

Requirements:

  • Currently enrolled in a Bachelor's degree program in Statistics, Data Science, Computer Science, Finance or related field.
  • Strong interest in strategic data-driven decision-making, with a passion for leveraging data to drive business outcomes and improve organizational performance.
  • Strong problem-solving skills and analytical skills with the ability to work with complex datasets.
  • Knowledge of data manipulation and analysis using programming languages such as SQL, Python or R. Experience with data querying and manipulation using SQL.
  • Familiarity with data visualization tools and techniques (e.g., Tableau, Power Bl). 

Time Commitment:

The maximum hour for this position is 34 hours per week during the summer (July to end of August). Afterward, the maximum hours will be reduced to 19 hours per week for the academic year (fall to end of spring 2026).