As a data scientist at Booz Allen, help turn complex data sets into useful information to solve global challenges across private and public sectors, from fraud detection to cancer research to national intelligence, by finding answers in the data.
Requirements
- 3+ years of experience with using programming languages to manipulate and analyze data, including Python, R, and SQL
- Experience with deploying and maintaining user-facing or user-accessible models
- Experience with data cleansing, data analytics, inferential statistics, programming, data visualization, and system integration to provide data solutions
- Experience with developing data visualizations, dashboards, or lightweight web applications to communicate key insights
- Knowledge of research design principles
- Knowledge of analytic methods and methodological tools used in applied mathematics, computer programming, or data visualization
- Ability to apply supervised and unsupervised machine learning algorithms on structured and unstructured datasets
Responsibilities
- use your leadership skills and data science expertise to create real-world impact
- 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
- guide teammates and lead the development of algorithms and systems
- use the right combination of tools and frameworks to turn sets of disparate data points into objective answers to advise your clients as they make informed decisions
- provide a deep understanding of the data, what it all means, and how it can be used
- use programming languages to manipulate and analyze data, including Python, R, and SQL
- deploying and maintaining user-facing or user-accessible models
Other
- TS/SCI clearance with a polygraph
- Bachelor’s degree
- Experience with project management, project planning, and technical documentation
- Knowledge of psychometric theory and assessment validation methodologies such as Item Response Theory and Factor Analysis
- Knowledge of data strategy and data governance
