Data Scientist

Data Scientist  Annapolis Junction, MD –

Full-Time TS/ SCI/Fullscope Poly Clearance

A data scientist will develop machine learning, data mining, statistical

and graph-based algorithms to analyze and make sense of datasets;

prototype or consider several algorithms and decide upon final model based

on suitable performance metrics; build models or develop experiments to

generate data when training or example datasets are unavailable; generate

reports and visualizations that summarize datasets and provide data-driven

insights to customers; partner with subject matter experts to translate

manual data analysis into automated analytics; implement prototype

algorithms within production frameworks for integration into analyst


  • Bachelor’s and Master’s degree or higher from an accredited college or

university in a quantitative discipline (e.g., statistics, mathematics,

operations research, engineering or computer science).

  • Ten years of experience analyzing datasets and developing analytics, and

ten years of experience programming with data analysis software such as R,

Python, SAS, or MATLAB.

  • Produce data visualizations that provide insight into dataset structure

and meaning

  • Work with subject matters experts (SMEs) to identify important

information in raw data and develop scripts that extract this information

from a variety of data formats (e.g., SQL tables, structured metadata,

network logs) Incorporate SME input into feature vectors suitable for

analytic development and testing

  • Translate customer qualitative analysis process and goals into

quantitative formulations that are coded into software prototypes

  • Develop and implement statistical, machine learning, and heuristic

techniques to create descriptive, predictive, and prescriptive analytics

  • Develop statistical tests to make data-driven recommendations and


  • Develop experiments to collect data or models to simulate data when

required data are unavailable

  • Develop feature vectors for input into machine learning algorithms
  • Identify the most appropriate algorithm for a given dataset and tune

input and model parameters

  • Evaluate and validate the performance of analytics using standard

techniques and metrics (e.g. cross validation, ROC curves, confusion


  • Oversee the development of individual analytic efforts and guide team in

the analytic development process

  • TS/ SCI/Fullscope Poly Clearance




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