Operational Data Scientist TS/SCI (FSP)

At IBM, work is more than a job, it’s a calling: To build. To design. To code. To consult. To collaborate with clients and teammates to deliver impactful solutions to solve meaningful problems at scale in complex mission environments. IBM has been building and applying advanced analytics, machine learning, and data-driven systems for decades, solving some of the most complex technical challenges long before they became industry buzzwords. That experience shapes how we approach today’s problems: with discipline, practicality, and a focus on delivering real-world outcomes. We’re looking for early-career data professionals who are ready to build strong technical capabilities and contribute to real mission problems. You bring a solid foundation and a desire to grow into a well-rounded technologist who can both build data systems and extract meaning from them. You may enter with a strength in data engineering or data science. What matters is your willingness to expand beyond it. In this role, you won’t be siloed, you’ll work across the full data lifecycle, contributing to how data is ingested, shaped, analyzed, and used. You’ll be part of a collaborative, high-performing team where expectations are high, ownership is shared, and growth is earned through delivery, working alongside experienced team members who actively support your development. This role is for someone who wants to build real systems, solve meaningful problems, and continuously improve alongside a team that values both contribution and growth. If you’re looking for a place where you can build strong technical capabilities, contribute early, and gain meaningful experience working on real mission problems, this is that opportunity as we help build the next generation of data capability in mission environments. *** US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. The Junior Data Engineer / Data Scientist is a hands-on technologist and analytical problem-solver who works in collaboration with team members while developing expertise across both data engineering and data science disciplines. The successful candidate will contribute to both data systems and analytical workflows, supporting delivery of capabilities that are technically sound, operationally practical, and aligned to mission outcomes. Clearance & Logistics: US Citizenship is required. Candidates must possess an active Top Secret/SCI (TS/SCI) clearance with a Full Scope Polygraph on Day 1 and be able to work onsite in the Washington, DC Metro area (Chantilly, VA). Work is performed in a secure environment with limited remote flexibility. Programming & Data Fundamentals: Hands-on experience with Python and SQL, including the ability to manipulate, transform, and analyze data. Candidates should demonstrate working knowledge of core data concepts, including data ingestion, transformation (ETL/ELT), and working with structured and unstructured data. Foundational Analytical & Processing: Demonstrated familiarity with statistical analysis or basic machine learning concepts, along with experience using tools such as Jupyter, Pandas, or similar data-focused libraries to explore and process data. Development Practices & Tooling:

Preferred technical and professional experience

Experience working with version control systems such as Git, and an understanding of writing clean, maintainable, and collaborative code in a team environment. Ways of Working: Demonstrates a mission-oriented mindset and an understanding of how technical outputs support real-world outcomes. Operates effectively in team-based environments with shared ownership and accountability. Adapts to evolving or ambiguous situations and demonstrates a consistent commitment to developing across both engineering and analytical domains.

Education

& Experience: Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics is preferred, or related technical discipline with 1-3 years of relevant professional experience, or a Master’s degree in related field with little to no professional experience. Equivalent practical experience will also be considered. Candidates must demonstrate the ability to apply academic or hands-on experience to real-world data challenges Candidates may enter the role with a lean towards either data engineering or analytics but should demonstrate exposure to both areas and a willingness to expand across the full data lifecycle. IC Sector Experience: 3+ years within the last 5 years supporting or architecting systems for that National

Security

or Defense sector, with exposure to air-gapped delivery and secure AI requirements. Data Engineering Exposure: Experience contributing to data pipelines or ETL/ELT workflows, with familiarity in working with datasets, data modeling, or integrating data from APIs and external sources. Exposure to improving data quality, reliability, or performance is a beneficial. Data Science & Analytical Foundations: Academic or project-based experience applying statistical analysis or machine learning techniques. Familiarity with tools such as scikit-learn, TensorFlow, PyTorch, or similar frameworks, along with the ability to explore data and identify meaningful patterns or trends. Cloud & Modern Data Environments: Experience creating visualizations, dashboards, or reporting outputs that help communicate insights to technical and non-technical audiences and support decision-making. Integration & Tooling: Familiarity with REST APIs, JSON-based data exchange, or system integrations. Exposure to containerization or deployment tools such as Docker or Kubernetes is beneficial. Demonstrated Application of Skills: Demonstrated project experience is highly valued. Candidates are encouraged to provide examples of relevant work (e.g., GitHub repositories, technical projects, or applied data work) that showcases their ability to build, analyze, and deliver practical solutions. Education & Experience: Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or related technical discipline with 1-3 years of relevant professional experience, or a Master’s degree in related field with little to no professional experience. Equivalent practical experience will also be considered. Candidates must demonstrate the ability to apply academic or hands-on experience to real-world data challenges United States Data & Analytics Professional Multiple Cities