E-Discovery Data Analyst

Job Description

Job Description

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:

The contractor shall provide an individual to perform as a
Government team member. The contractor shall perform:
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
ServiceNow 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 ServiceNow 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.