Data Scientist, Mid

Job Overview

Data Scientist, Mid-level. Supporting a Space Force program, you will contribute to analytic development and mission‑focused modernization across space-based GEOINT environments. You will work within a multi‑disciplinary team of data engineers, mission analysts, and cloud engineers to design, build, validate, and deploy analytic models that enhance decision advantage for operational users. You will help build end‑to‑end analytic workflows, from ingesting complex mission data to developing repeatable models and deploying them into cloud‑native environments.

You will translate mission objectives into technical requirements, implement analytic prototypes, and ensure outputs meet mission timelines, accuracy expectations, and operational usability standards.

• Design, implement, and validate analytics supporting multi‑INT, geospatial, and space‑system data.
• Build and evaluate AI/ML models using libraries such as Tensor Flow, PyTorch, and Scikit‑learn.
• Contribute to data engineering workflows, including ingestion, transformation, QC, and storage of large mission datasets.
• Develop analytic prototypes and support their operationalization into cloud‑native platforms such as AWS, Azure, or hybrid government cloud.
• Integrate models and analytics into mission‑critical workflows, supporting near‑real‑time data processing.
• Perform feature engineering, model training, hyperparameter tuning, and baseline creation for anomaly detection and system‑behaviour characterization.
• Support multi‑INT data fusion, including GEOINT, SIGINT, MTI, ISR, or related mission data types.
• Document analytic methods, model assumptions, performance metrics, and validation frameworks.
• Contribute to technical deliverables and analytic CONOPs in collaboration with senior data science leadership.
• Collaborate with operators and mission partners to ensure analytics align with mission needs and timelines.
• Provide mentorship to junior analysts and support continuous improvement of analytic best practices.

• Experience in data science, applied analytics, or ML.
• Experience working with geospatial or multi‑INT datasets and developing and validating AI or ML models.
• Experience with distributed compute environments and handling high‑volume mission data.
• Experience integrating models or analytics into production or mission workflows.
• Experience with cloud‑native ML platforms such as AWS Sage Maker or Azure ML.
• Experience developing queries, transformations, and operational analytics in SQL and Python.
• Ability to support analytic CONOPs, translate mission requirements, and document technical approaches.
• Ability to collaborate in a high‑tempo environment and communicate technical concepts to mission stakeholders.
• Top Secret clearance.
• HS diploma or GED.

• Experience with IC or DoD analytics, including within DIA, CCMDs, USSPACECOM, or mission‑partner organizations.
• Experience with FADE or MIST, JEMA, or operator‑facing mission‑system analytics.
• Experience building models for MTI, ISR such as SAR and EO, or space‑domain analytics.
• Experience developing or supporting enterprise‑level data architectures, catalogs, or metadata frameworks.
• TS/SCI clearance with a polygraph.
• Professional certifications such as Google Professional Machine Learning Engineer, Azure Data Scientist Associate, AWS Machine Learning - Specialty, or Tensor Flow Developer Certification.

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information;
Top Secret clearance is required.

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.