Data Scientist, Mid

Booz Allen Hamilton•Arlington, VA

7d•Remote

About The Position

Are you excited at the prospect of unlocking the secrets held by a data set? Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? In an increasingly connected world, massive amounts of structured and unstructured data open up new opportunities. As a data scientist, you can 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 know the answers are in the data. We have an opportunity for you to use your analytical skills to improve our business. You’ll work closely with your customer to understand their questions and needs, and then dig into their data-rich environment to find the pieces of their information puzzle. You’ll apply analytical skills and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help clients make informed decisions. You’ll provide your customer with a deep understanding of their data, what it all means, and how they can use it. Join us as we use data science for good in advising. Join us. The world can’t wait.

Requirements

2+ years of experience in data science in a professional work environment
Experience with machine learning, data mining, statistics, or graph algorithms in academic or internship environments
Experience in data gathering, analytical, and problem-solving work
Knowledge of an object-oriented language, including Java, C++, C#, or Python
Knowledge of SQL
Secret clearance
Bachelor’s degree in a STEM field

Nice To Haves

Experience with using R, Perl, Python, Tableau, SAS, or SPSS for data analysis
Experience with AWS, including S3 and Lambda
Possession of excellent verbal and written communication skills
Possession of excellent interpersonal skills

Responsibilities

Work closely with customers to understand their questions and needs.
Dig into data-rich environments to find pieces of information.
Apply analytical skills and use the right combination of tools and frameworks to turn disparate data points into objective answers.
Help clients make informed decisions.
Provide customers with a deep understanding of their data, its meaning, and how to use it.