Data Science Intern, temporary

Responsibilities*

The DSDS student intern, temporary will assist in ensuring the smooth progress of our AI article tagging project. The intern will help streamline the tagging process, increase the precision of our tagging models, and ultimately enhance the overall quality of our article database.

The intern will be expected to work 15-20 hours per week and will take on the following responsibilities:

• The intern will review a significant volume of tagged and untagged articles, ensuring they meet our quality standards. This review process is crucial in maintaining the integrity of our dataset and providing feedback for further refinement. The intern will be responsible for ensuring that tags are applied consistently and appropriately reflect the content of each article.
• The intern will participate in testing the AI models by simulating user interactions and verifying that the tagging system meets the specified requirements. Their feedback will be essential in identifying any areas that need adjustment or improvement.
• The intern will analyze the performance of AI models by comparing model predictions against established benchmarks. They will contribute insights on how to optimize algorithms and improve their accuracy in tagging articles.
• Maintain detailed documentation of their findings and communicate insights to the team. The intern will produce regular reports on the tagging process and the progress of model evaluations.
  
  
  

Data Management and Knowledge Generation (50%)

• Use a strong proficiency with SQL as well as a working knowledge of Python, R, Spark, and/or Google Workspace to gather, create, and use datasets for the purposes of identifying, classifying, and refining prospect lists for fundraising activities.
• Maintain data dictionaries to support knowledge transfer.
• Use other tools such as regular expressions, web APIs, and programming languages like Spark or Python to develop custom programs for scraping, cleaning, and standardizing unstructured data sources such as websites, text documents, and entity relationships.
• Work with the OUD Development Services teams, Marketing and Communications teams, as well as other relevant University and business intelligence resources to better understand and use internal data.
  
  
  

Data Analysis, Data Mining, and Statistical Model Building (25%)

• Assist with the search for explanations and underlying causes.
• Use various software tools including, but not limited to, Python, R, Google Workspace, SQL Server, AWS, Databricks, Git and Tableau to analyze and present the data analyses for specific development purposes.
• Synthesize and disseminate results through written reports, maps, charts, graphs and presentations.
  
  
  

Analytics Program Outreach (20%)

• Work with University fundraising staff as an internal consultant to define analytics needs and guide the team to meet those needs.
• Present work to internal and external audiences.
  
  
  

Perform other duties as assigned (5%)

Required Qualifications*

• Exposure to and deep interest in AI tools
• Exposure to cloud-based analytics tools
• Exposure to developing interactive, reusable and self-service online analytics tools
• Exposure to cloud-based analytics tools
• Familiarity with prospect development and major gift data
• Demonstrated competencies in information retrieval, computer science, data analysis, or similar fields
• The desire and ability to do serious data munging and data wrangling is essential. At minimum, we expect demonstrated experience with SQL plus knowledge of another data preparation language. Must be able to use these tools to merge large datasets, locate and clean messy records, recode missing values, convert between data formats, and construct standardized datasets for wider use
• Proven ability to turn data into action, emphasizing the ability to understand and utilize large datasets representing complex phenomena and to present findings in a clear and cohesive manner. Must demonstrate the ability to present information in formal and informal settings and impart understanding of complex ideas to others
• The ability to synthesize and translate data into meaningful stories
• Persistence, curiosity, and teamwork skills to collaborate with technical and non-technical peers
  
  
  

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.