Data Scientist, Senior

Booz Allen Hamilton•Alexandria, VA

8d•$99,000 - $225,000•Onsite

About The Position

As a Senior Data Scientist at Booz Allen, you will use data science expertise and leadership skills to help clients turn complex, structured and unstructured data into useful information. You will work closely with clients to understand their questions and needs, analyze data-rich environments, and develop algorithms and systems. You will apply appropriate tools and frameworks to transform disparate data into objective answers that support informed decisions, providing a clear understanding of what the data means and how it can be used. The role supports data science applications across private and public sectors, including areas such as fraud detection, cancer research, and national intelligence. The role is based in Alexandria, Virginia, and is not listed as remote. An active TS/SCI clearance is required, and candidates must be willing to take a polygraph exam. Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

Requirements

Experience working with AI/ML technologies and data systems.
Experience working with multiple file types, including geospatial file formats, JSON, and XML.
Experience conducting quantitative analysis, developing visualizations, and processing complex data to create data-driven insights.
Experience developing in languages such as Python for data cleaning and manipulation.
Active TS/SCI clearance and willingness to take a polygraph exam.
One of the following education and experience combinations: high school diploma or GED and 10 or more years of data science experience; bachelor's degree and 7 or more years of data science experience; or master's degree and 5 or more years of data science experience.

Nice To Haves

Experience applying NLP algorithms to extract data from documents.
Experience with enterprise analytic modernization efforts such as SOM, Computer Vision, automated collection, or automated reporting, along with data standardization best practices.
Expertise in mathematics, statistics, and quantitative analysis.
Experience with analytic techniques such as classification, regression, clustering, data reduction, and causal modeling.

Responsibilities

Work with clients to understand their questions and needs.
Analyze complex data sets in data-rich environments to find useful information.
Guide teammates and lead development of algorithms and systems.
Select tools and frameworks to transform disparate data into objective answers that support client decision-making.
Develop data-driven insights through quantitative analysis, visualization, and processing complex data.