Data Scientist, Mid

Booz Allen Hamilton•Arlington, VA

About The Position

As a Data Scientist at Booz Allen, you will analyze structured and unstructured data to help solve challenges across private and public sectors. You will work closely with clients to understand their questions and needs, explore data-rich environments, and collaborate with teammates to develop algorithms and systems. You will select appropriate tools and frameworks to turn disparate data into objective answers that support informed decisions, while explaining what the data means and how it can be used.

Requirements

  • Experience with data exploration, data cleaning, data analysis, data visualization, data science, or data mining.
  • Experience with statistical and general-purpose programming languages for data analysis, such as Python, R, SQL, AWS, or HTML.
  • Knowledge of statistical analysis, predictive modeling, and machine learning methods.
  • Ability to design and develop automated analytic software, techniques, and algorithms.
  • Active TS/SCI clearance with a polygraph is required.
  • Bachelor's degree and 3+ years of experience with data science, or 7+ years of experience with data science in lieu of a degree.

Nice To Haves

  • Experience with intelligence or operations analysis in the DoD or Intelligence Community.
  • Experience working in a Joint Staff environment.
  • Experience creating ETL pipelines, including querying APIs, cleaning and conditioning data, and creating schemas for data storage.
  • Knowledge of version control tools, including Git, GitLab, GitHub, or Bitbucket.
  • Knowledge of DevOps, including CI/CD pipelines and Jenkins.
  • Ability to use data visualization tools, including COTS software such as Tableau, Power BI, or ArcGIS, or FOSS libraries such as seaborn, matplotlib, or ggplot.

Responsibilities

  • Work with clients to understand their questions and needs.
  • Explore data-rich environments to identify useful information.
  • Collaborate with teammates to develop algorithms and systems.
  • Select tools and frameworks to transform disparate data into objective answers.
  • Provide an understanding of data, its meaning, and its potential uses.

Benefits

  • Health, life, and disability benefits
  • Financial and retirement benefits
  • Paid leave
  • Professional development
  • Tuition assistance
  • Work-life programs
  • Dependent care
  • Recognition awards program
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