Data Scientist & AI Engineer, Mid

Booz Allen Hamilton•Bethesda, MD

2d•$77,600 - $176,000•Hybrid

About The Position

Are you ready to embark on a journey where your skills in data and artificial intelligence will drive innovation and propel businesses into the future? Are you fascinated by the possibilities presented by artificial intelligence advances? In an increasingly connected world, massive amounts of structured and unstructured data open up new opportunities. As an aspiring data scientist AI engineer, you know you can help turn these complex data sets into useful information to solve global challenges. Across private and public sectors — from fraud detection to cancer research, to national intelligence — you see data scientists turning data into actions and you want to be part of the team. As a data scientist on our team, you’ll use your analytical skills to help create real-world impact. You’ll work closely with clients to understand their questions and needs, and then dig into their data-rich environments to find the pieces of their information puzzle. You’ll work with and learn from your teammates as you develop algorithms and systems. You’ll use the right combination of tools and frameworks to turn sets of disparate data points into objective answers so that your clients can make informed decisions. If you are driven by curiosity, thrive in a fast-paced setting, and have a deep fascination with the potential of AI, this is the place where you can make a significant impact. Join us, and be part of a team that's not only shaping the future but also pushing the boundaries of what's possible. Join us. The world can’t wait.

Requirements

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 to collaboratively develop reliable AI solutions
Ability to query, process, and build data pipelines for large, complex datasets using big data technologies
Ability to evaluate AI models using appropriate performance metrics, validation methods, and error analyses to assess accuracy, robustness, bias, fairness, and fitness for the intended use case
Public Trust
Bachelor's degree in Computer Science, Machine Learning, Data Science, Engineering, or Mathematics

Nice To Haves

Experience with AWS or other cloud services
Experience with program automation, CI and CD, DevSecOps, or Agile
Experience with healthcare or medical device industry data
Experience with Agile methodologies and best practices
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 appropriate comparison groups, and determine the data and methods needed to assess an AI solution before development begins
Master’s degree preferred; Doctorate degree a plus

Responsibilities

Use analytical skills to help create real-world impact.
Work closely with clients to understand their questions and needs.
Dig into data-rich environments to find pieces of information.
Develop algorithms and systems.
Use the right combination of tools and frameworks to turn sets of disparate data points into objective answers.
Leverage statistical programming languages to develop predictive data models, quantitative analyses, and data visualizations.
Apply Artificial Intelligence, including Machine Learning, Agentic AI, Natural Language Processing, and applied use of Large Language Models.
Develop front-end applications using React or Python-based frameworks, such as Streamlit to build interactive, user-facing data applications.
Build LLM-powered applications and autonomous agents using generative AI and agentic AI libraries and frameworks.
Write efficient, clean, and maintainable code, using Git, testing, and code reviews to collaboratively develop reliable AI solutions.
Query, process, and build data pipelines for large, complex datasets using big data technologies.
Evaluate AI models using appropriate performance metrics, validation methods, and error analyses to assess accuracy, robustness, bias, fairness, and fitness for the intended use case.