Data Scientist

Booz Allen Hamilton•Arlington, VA

1d•$77,600 - $176,000•Hybrid

About The Position

As a Data Scientist at Booz Allen, you will use data science and analytical skills to turn complex structured and unstructured data into useful information that helps clients make informed decisions and address challenges across public and private sectors. You will work closely with clients to understand their questions and needs, explore data-rich environments, develop algorithms and systems, and apply appropriate tools and frameworks to derive objective answers and explain what the data means and how it can be used. The role is hybrid and based in Arlington, Virginia, with additional locations in Alexandria, Virginia, and Washington, D.C.

Requirements

At least 2 years of experience with data exploration, data cleaning, data analysis, data visualization, or data mining.
At least 2 years of experience with statistical and general-purpose programming languages for data analysis.
Experience analyzing structured and unstructured data sources.
Experience developing predictive data models, quantitative analyses, and visualizations of targeted data sources.
Knowledge of machine learning, artificial intelligence, or natural language processing (NLP).
Knowledge of text mining or machine learning techniques.
Secret clearance is required.
Bachelor’s degree.

Nice To Haves

At least 2 years of experience developing algorithms using R, Python, SQL, or NoSQL.
At least 2 years of experience with distributed data or computing tools, including Databricks, MapReduce, Hadoop, Hive, EMR, Kafka, Apache Spark, Gurobi, or MySQL.
At least 2 years of experience with machine learning, AI, or NLP.
Experience with Palantir Foundry.
Experience with visualization packages, including Plotly, Seaborn, or ggplot2.
TS/SCI clearance with a polygraph.
Master’s degree.

Responsibilities

Work with clients to understand their questions and needs.
Explore and analyze structured and unstructured data to identify useful information.
Develop algorithms, predictive data models, and systems using suitable tools and frameworks.
Conduct quantitative analyses and visualize targeted data sources.
Translate data into objective findings that help clients make informed decisions.
Explain the meaning and potential uses of data to clients.