Intermediate Data Scientist

Position Summary

MITRE is seeking an Intermediate Data Scientist to help turn large volumes of Department of Justice (DOJ) sponsor data into meaningful insights and actionable recommendations that advance the sponsor's mission. Working under the guidance of senior technical staff and in coordination with project leadership, the selected candidate will use hands-on coding and data analysis to investigate mission questions, identify opportunities for improvement, and develop evidence supporting recommended actions.

The role includes preparing reproducible analyses, visualizations, models, and presentations that help sponsors understand findings and put recommendations into practice. The supporting project operates at the intersection of mission, operations, and artificial intelligence. This position offers a recent masters graduate the opportunity to develop technical skills while contributing to real-world mission challenges. This role requires on-site presence consistent with corporate policy, between MITRE space and Sponsor space in the District of Columbia. Occasional travel may be required.

Roles & Responsibilities

• Work with senior technical staff and project leadership to understand sponsor needs and translate mission questions into focused analytical tasks.
• Use Python, SQL, and related tools to access, clean, combine, and analyze large datasets.
• Explore data to identify patterns, trends, and opportunities to improve sponsor capabilities and operations.
• Apply statistical methods and develop analytical models, with guidance, to assess findings and support recommendations with sound evidence.
• Create visualizations and dashboards using tools such as Power BI to make findings understandable and useful.
• Help develop actionable recommendations, assess their expected benefits and limitations, and identify how the sponsor could put them into practice.
• Prepare reports and presentations that explain the evidence behind recommendations and help sponsors make informed decisions and adopt improvements.
• Maintain organized code, document data sources and analytical methods, and use version control so that analyses can be reviewed, reproduced, and updated.
• Participate in peer reviews, incorporate feedback, and communicate progress, questions, and data limitations to the team.
• Build familiarity with the sponsor's mission and relevant technologies in identity management, biometrics, information management, and artificial intelligence.

Basic Qualifications

• U.S. citizenship is required as this position requires having and maintaining a Top-Secret clearance.
• Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related technical field.
• Foundational experience using Python or a comparable programming language for data analysis, demonstrated through coursework, academic projects, internships, research, or personal projects.
• Familiarity with SQL and relational databases.
• Understanding of basic statistical concepts and methods for exploring, analyzing, and interpreting data.
• Ability to communicate analytical findings clearly through writing, visualizations, and presentations.
• Organizational skills and attention to detail sufficient to maintain clear documentation and reproducible analytical work.
• Ability to work collaboratively, incorporate feedback, and complete assigned tasks under the guidance of experienced staff.
• Ability to obtain accounts on the sponsor's unclassified and classified networks.
• Ability to meet on-site requirements consistent with corporate policy and travel occasionally as needed.
• No prior full-time professional experience is required.

Preferred Qualifications

• Using Python and SQL to prepare and analyze data.
• Creating dashboards or visualizations in Power BI or Tableau.
• Using Git or other version control tools to manage code changes.
• Applying statistical or machine learning methods to practical questions and evaluating the reliability of results.
• Turning analytical findings into recommendations and presenting the supporting evidence.
• Exposure to biometrics, identity matching, name matching, or human-language technologies.