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E-Discovery Data Analyst

Job in Washington, District of Columbia, 20022, USA
Listing for: Executive Decision LLC
Full Time position
Listed on 2026-08-20
Job specializations:
  • IT/Tech
    Data Analyst, Information Security & Data Protection
Salary/Wage Range or Industry Benchmark: 90000 - 140000 USD Yearly USD 90000.00 140000.00 YEAR
Job Description & How to Apply Below

We are looking for a detail-oriented and technically proficient Information Technology Specialist with extensive experience in Litigation Support and eDiscovery within federal environments. Must be adept at providing expert advice and technical assistance to legal teams, ensuring seamless integration of technological capabilities throughout case investigations and litigation processes. Skilled in database management, electronic data processing, and courtroom technology support. Proven track record of delivering high-quality customer support, training, and system security management.

Summary:
  • a) Perform data analytic services for NSD case and program level data analytics projects.
  • b) Provide input and solutions utilizing contemporary industry best practices to assist NSD with its use of technology assisted review within investigation and prosecution through proactive data analytics litigation projects.
  • c) Provide input and solutions to assist NSD with data governance and information management through maturity of the Data Analytics portfolio.
  • d) Enhance NSD data collection management to include gap analysis, enterprise content search and analysis, and structured analytics to increase our ability to manage responsive requests. NSD is also seeking to build out a dashboard in Service Now to track our Responsive Data Collections, including Capstones with the ability to link individual custodians to tickets for enhanced governance in this area.
  • e) Implement Litigation Support information security principles and methods.
  • f) Perform Early Data Assessment of Electronically Stored Information and custom analysis, including domain parsing, gap analysis and name normalization; and notify the eLit&DS Chief of any deficiencies in incoming productions.
  • g) Use Relativity, IPRO Eclipse, Everlaw, Nuix, and/or other data analytics tools, to prepare analysis of information sources, timeline development, communication patterns, and data quality controls.
  • h) Develop data dashboards within case repositories (e,g, Relativity or Everlaw) and/or using COTS data analysis tools (e.g. Power BI) to support case team review.
  • i) Develop program level dashboards to track legal operations metrics which will support evidence-based decision making.
  • j) Complete task documentation including, quality control checklists, workflow process documentation and explanations.
  • k) Support the development of technology assisted review projects that will identify seed sets and sampling of relevancy rates and performance metrics to assist with culling voluminous electronic evidence. Perform quality control on these projects.
Additional:
  • Utilize advanced eDiscovery platforms to load, process, manage, and produce electronically stored information (ESI) for legal cases.
  • Provide input and innovative solutions to enhance the use of technology-assisted review within investigations and prosecutions.
  • Assist with data governance and information management, contributing to the maturity of the Data Analytics portfolio.
  • Ensuring the accurate location, organization, and production of ESI in response to subpoenas, litigation discovery requests, FOIA requests, congressional inquiries, and inter-agency document requests.
  • Develop and maintain a dashboard in Service Now to track Responsive Data Collections, linking individual custodians to tickets for improved governance.
  • Perform Early Data Assessment of Electronically Stored Information, including domain parsing, gap analysis, and name normalization; identify and report deficiencies.
  • Utilize Relativity, IPRO Eclipse SE Admin/Desktop, Everlaw, Nuix, and other data analytics tools to prepare analyses of information sources, develop timelines, communication patterns, and ensure data quality.
  • Complete task documentation, including quality control checklists and workflow process documentation.
  • Support technology-assisted review projects, identifying seed sets, sampling relevancy rates, and performance metrics, and performing quality control.
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