Data Scientist, Mid in Hampton, VA at Booz Allen Hamilton Inc.

Date Posted: 5/28/2018

Job Snapshot

  • Employee Type:
    Full-Time
  • Location:
    Hampton, VA
  • Job Type:
    Science
  • Experience:
    Not Specified
  • Date Posted:
    5/28/2018

Job Description

Job Number: R0024788

Data Scientist, Mid

Key Role:

Obtain data through advanced computerized models, extrapolate data patterns through advanced algorithms, and develop analytics to explain how the mathematical information will predict future patterns or behavior. Present how to best business models to generate future trends to managers and discover patterns and previously hidden insights. Apply broad domain expertise to comprehend data origins and context to ensure data consistency, merge data sources together, and help others gain better comprehension of data. Leverage mathematical modeling and machine learning expertise within a risk analysis framework to explore and examine data from multiple disparate sources with the goal of discovering patterns and previously hidden insights. 


Basic Qualifications:

-2+ years of experience in the data science or analytics field

-Experience in working with machine learning, data mining, and statistics

-Experience with the analysis of data and creation of data-driven visualizations

-Ability to create reports and present findings based on statistical analysis

-Ability to develop persistent monitoring applications for statistical or machine learning processes using R, Python, or SAS
-Ability to obtain a security clearance

-MA or MS degree


Additional Qualifications:

-Experience with Big Data programming technologies, including Hadoop, MapReduce, Accumulo, Cassandra, HBase, R, Mahout, Pig, and Hive-BA

-Experience with GEOINT data, formats, structures, and standards

-PhD degree in CS, Physics, Engineering, Statistics, or Mathematics a plus
 

Clearance:
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information.

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