Data Scientist, Mid

Booz Allen Hamilton•Springfield, VA

20h•Remote

About The Position

As a mid-level data scientist 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. In this role, you will support the development of statistical baselines, anomaly detection workflows, and multi-INT fusion analytics. You will work with tools such as Python, SQL, FADE or MIST, JEMA, and modern AI / ML libraries. You will collaborate with government partners, operators, and senior data scientists to deliver high-quality analytics tailored for real-time and near-real-time operational use.

Requirements

Experience in data science, applied analytics, or ML
Experience working with geospatial or multi-INT datasets, and developing and validating AI / 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 SageMaker 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
Active TS/SCI clearance; willingness to take a polygraph exam
HS diploma or GED

Nice To Haves

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 TensorFlow Developer Certification

Responsibilities

Design, implement, and validate analytics supporting multi-INT, geospatial, and space-system data.
Build and evaluate AI / ML models using libraries such as TensorFlow, 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-behavior 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.