Overview

LMI is seeking a data scientist to assist in developing, testing, and fielding algorithms in support of a supply chain risk program for the Department of Defense.

At LMI, we’re reimagining the path from insight to outcome at The New Speed of Possible™. Combining a legacy of over 60 years of federal expertise with our innovation ecosystem, we minimize time to value and accelerate mission success. We energize the brightest minds with emerging technologies to inspire creative solutioning and push the boundaries of capability. LMI advances the pace of progress, enabling our customers to thrive while adapting to evolving mission needs. 

Responsibilities

  • Write python, pySpark, and SQL code to prepare and analyze data
  • Leverage broad familiarity with data science concepts to help streamline analysis of supply chain-relevant data
  • Work closely with data engineers, UI developers, and subject matter experts to develop and deploy data science methods in support of an evolving software suite
  • Work comfortably in a Databricks environment, where most code is developed, tested, and deployed via notebooks
  • Execute on data science tasking in support of multiple teams, coordinating prioritization across them as needed
  • Quickly learn, and be excited to leverage, novel data science techniques to solve real-world challenges involving large scale, often messy data sets

Qualifications

  • Bachelor's degree in Computer Science or related field and/or equivalent work experience
  • 3+ years of experience as a data scientist
  • Experience with:
    • Agile-based development
    • Python, Spark, notebooks
    • Data Bricks or similar environment
    • Scikit-learn or similar python packages
  • Effective analytical, conceptual, and problem-solving skills
  • Active DoD Secret clearance required (Top Secret clearance highly desired)
  • Part-time onsite client support in the Washington, DC metro area

Location

Washington, DC, United States

Job Overview
Job Posted:
6 months ago
Job Expires:
Job Type
Full Time

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