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Data Scientist, AI Engineer – Mid
Booz Allen Hamilton. Develop predictive data models, quantitative analyses, and data visualizations .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing predictive data models and quantitative analyses using statistical programming languages, while leveraging AI technologies such as Machine Learning and Natural Language Processing. Proficient in building interactive data applications and evaluating AI models for performance and fairness.
Highest-signal resume keywords
Predictive Data ModelingMachine LearningNatural Language ProcessingReact Front-End DevelopmentData Pipeline Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical Programming LanguagesData VisualizationAlgorithm DevelopmentAI Model EvaluationBig Data Technologies
Soft Skills
Client CollaborationProblem Solving
Tools & Technologies
GitAWSStreamlitCI/CDDevSecOps
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree PreferredDoctorate Degree a Plus
Industry Keywords
Healthcare DataMedical Device Industry DataGenerative AIAgentic AIAI-Assisted Development Tools
Tech Stack
Tools & technologiesAWSCloudPythonReact
About the role
Key responsibilities & impact- Develop predictive data models, quantitative analyses, and data visualizations
- Work closely with clients to understand their questions and needs
- Analyze data-rich environments and identify useful information from complex datasets
- Develop algorithms and systems with teammates
- Select tools and frameworks to transform disparate data into objective answers
- Build interactive, user-facing data applications
- Build LLM-powered applications and autonomous agents
- Query, process, and build data pipelines for large, complex datasets
- Evaluate AI models for accuracy, robustness, bias, fairness, and fitness for intended use cases
- Collaboratively develop reliable AI solutions using coding standards, Git, testing, and code reviews
Requirements
What you’ll need- 3+ years of experience leveraging statistical programming languages to develop predictive data models, quantitative analyses, and data visualizations
- 2+ years of experience in Artificial Intelligence, including Machine Learning, Agentic AI, Natural Language Processing, and applied use of Large Language Models
- Experience with front-end development using React or Python-based frameworks, such as Streamlit, to build interactive, user-facing data applications
- Experience with generative AI and agentic AI libraries and frameworks for building LLM-powered applications and autonomous agents
- Experience writing efficient, clean, and maintainable code using Git, testing, and code reviews
- Ability to query, process, and build data pipelines for large, complex datasets using big data technologies
- Ability to evaluate AI models using performance metrics, validation methods, and error analyses
- Public Trust determination required
- Bachelor's degree in Computer Science, Machine Learning, Data Science, Engineering, or Mathematics
- Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client
- Experience with AWS or other cloud services
- Experience with program automation, CI/CD, DevSecOps, or Agile
- Experience with healthcare or medical device industry data
- Experience using AI-assisted development tools like Claude Code, Cursor, or OpenCode
- Ability to apply experimental design principles to define evaluation criteria, establish baselines, identify comparison groups, and determine data and methods for assessing AI solutions
- Master's degree preferred; Doctorate degree a plus
Benefits
Comp & perks- Health benefits
- Life insurance
- Disability benefits
- Financial benefits
- Retirement benefits
- Paid leave
- Professional development
- Tuition assistance
- Work-life programs
- Dependent care
- Recognition awards program
- Identity verification and fraud prevention process