CBRN Defense Data Scientist

SAIC•Washington, DC
•Onsite

About The Position

Seeking a CBRN Defense Data Scientist to work in cross-functional teams with data at all stages of the analysis lifecycle to derive actionable insight. This role involves translating mission needs into an end-to-end analytical approach to achieve results. The position performs pre-analytics tasks such as data collection, understanding, cleansing, integration, storage, and retrieval. It also involves determining appropriate analytics based on data and desired outcomes, utilizing techniques like feature detection, statistics, data mining, predictive modeling, machine learning, natural language processing, and business intelligence. The role requires interpreting the validity of results and communicating their meaning. Familiarity with data wrangling, analytics, and visualization software and programming languages, including analytics methods for big data, is necessary. A scientific approach to generate value from data, verifying results at each step, is expected. This position is on-site in Washington, DC.

Requirements

  • Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience.
  • Familiarity with data wrangling, analytics, and visualization software and programming languages, including analytics methods for big data.

Responsibilities

  • Works in cross-functional teams with data at all stages of the analysis lifecycle to derive actionable insight.
  • Translates mission needs into an end-to-end analytical approach to achieve results.
  • Performs the pre-analytics areas of data collection and understanding, data cleansing and integration, and data storage and retrieval.
  • Determines the appropriate analytics based on the data and the desired outcomes, using techniques including feature detection, statistics, data mining, predictive modeling, machine learning, natural language processing, and business intelligence.
  • Interprets the validity of results and communicates the meaning of those results.
  • Follows a scientific approach to generate value from data, verifying results at each step.
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