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# Data Scientist, Mid

- **Company:** Booz Allen Hamilton Inc.
- **Location:** Springfield, VA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Information Engineering, Data Fusion, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Cloud Platform System, Feature Engineering, Data Ingestion, Pytorch, Scikit Learn, Machine Learning Operations
- **Published:** August 11, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/data-scientist-mid-springfield-va-usa-58897048

## About the Role

hybrid analytics into mission-critical workflows for near-real-time processing * Perform feature engineering, model training, and hyperparameter tuning for anomaly detection * Support MTI, ISR, and other mission data fusion * Document methods, performance metrics, and validation frameworks * Collaborate on technical deliverables and CONOPs with senior data science leadership * Mentor junior analysts and promote analytic best practices * Collaborate with operators and mission partners to meet timelines Tasks * Experience in data science, analytics, or ML * Experience with geospatial or multi-INT datasets and validating AI/ML models * Experience with distributed compute environments and handling high-volume mission data * Experience integrating models/ analytics into production or mission workflows * Experience developing queries, transformations, and operational analytics in SQL and Python * Ability to translate mission requirements and document technical approaches * Ability to aaaaaaaa
and in a high-tempo environment and communicate with mission stakeholders * Top Secret clearance * HS diploma or GED Key requirements * health benefits * life benefits * disability benefits * retirement benefits * paid leave * professional development and tuition assistance

## Description

Experteer Overview As a mid-level data scientist supporting a Space Force program, you design, validate, and deploy analytic models to enhance decision-making for space-based operations. You work in a cross-functional team to build end-to-end analytics-from data ingestion to cloud deployment-focusing on real-time and near-real-time mission needs. You contribute to multi-INT fusion, geospatial analytics, and anomaly detection, using modern AI/ML tools to support mission objectives and operator workflows. This role offers impact at scale within a mission-driven, collaborative environment. Compensation / Benefits * Design and validate analytics for multi-INT, geospatial, and space-system data * Build and evaluate AI/ML models with TensorFlow, PyTorch, Scikit-learn * Contribute to data engineering workflows: ingestion, transformation, QC, storage of large datasets * Develop analytic prototypes and operationalize them in cloud-native platforms (AWS, Azure, hybrid government cloud) * Integrate analytics into mission-critical workflows for near-real-time processing * Perform feature engineering, model training, and hyperparameter tuning for anomaly detection * Support MTI, ISR, and other mission data fusion * Document methods, performance metrics, and validation frameworks * Collaborate on technical deliverables and CONOPs with senior data science leadership * Mentor junior analysts and promote analytic best practices * Collaborate with operators and mission partners to meet timelines Tasks * Experience in data science, analytics, or ML * Experience with geospatial or multi-INT datasets and validating AI/ML models * Experience with distributed compute environments and handling high-volume mission data * Experience integrating models/ analytics into production or mission workflows * Experience developing queries, transformations, and operational analytics in SQL and Python * Ability to translate mission requirements and document technical approaches * Ability to collaborate in a high-tempo environment and communicate with mission stakeholders * Top Secret clearance * HS diploma or GED Key requirements * health benefits * life benefits * disability benefits * retirement benefits * paid leave * professional development and tuition assistance


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