Federal Data Engineering Co-Op: 2027 is a role within the US Federal team focused on delivering secure, mission-critical technology solutions for government agencies. You will work with federal, state, and local clients while developing expertise in government compliance and security standards. Day-to-day responsibilities include performing analytical support using statistical methods to predict behaviors, building data pipelines, and creating reusable programs to cleanse, integrate, and model data. You will also communicate complex findings to both technical and non-technical audiences. The role requires proficiency in Python or other scripting languages, with additional experience involving SQL, Spark, cloud platforms like IBM Cloud, Azure, or AWS, and machine learning libraries such as scikit-learn, SciPy, pandas, and PyTorch. This position addresses the specific challenge of providing secure data transformation and integration for public service missions.
Apply statistical methods and analytical rigor to predict behaviors for client projects.
Write efficient, reusable programs to cleanse, integrate, and model data.
Build data pipelines using Python to extract and transform data from various repositories.
Utilize cloud platforms and ETL tools to manage data integration tasks.
Communicate complex technical findings to both technical and non-technical audiences.
Deliver secure technology solutions that meet government compliance and security standards.
Maintain a federal security clearance while working on mission-critical government projects.
What we're looking for
Must have a High School Diploma or GED.
Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, IST, or a related field.
Must have the ability to obtain and maintain a Federal security clearance.
Familiarity with one or more scripting languages (Python preferred) or a proven computer science foundation.
Strong interpersonal skills for collaboration and managing dynamic workloads in an agile environment.
Demonstrated leadership experience and the ability to communicate effectively through active listening.
Availability to work on-site in University Park, PA, for up to 20 hours per week during the academic year and up to 40 hours during breaks.
Familiarity with statistical analysis, data mining, databases (SQL), data engineering tools, cloud platforms, or machine learning libraries (preferred).