Lead Data Analyst – OPUS

Capgemini Engineering

Lead Data Analyst specializing in advanced data analytics at Accelint. Collaborate with teams to drive decision-making based on predictive analysis and readiness models.

Posted 5/16/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $111,000 - $144,000 per yearWebsite

About the role

Key responsibilities & impact

Lead advanced data analytics, statistical modeling, and predictive analysis initiatives to support readiness based sparing models to support decision-making and strategic planning.
Partner with senior stakeholders to define analytical objectives, shape problem statements, and translate business challenges into actionable, data-driven strategies.
Enforce, maintain and contribute process improvements to documented enterprise data definitions, business rules, governance frameworks, and data quality standards.
Provide technical leadership and mentorship to junior analysts, supporting skill development and analytical best practices.
Serve as a trusted advisor and subject matter expert on data analytics methodologies, tools, and advanced analytical techniques.
Contribute technical expertise in data needed and structure to develop and model the simulation to identify the most effective option on the readiness cost curve.
Participate in planning sessions to acquire detailed information develop data pipeline architecture that align with project requirements.
Extract supporting data from identified tools, review available supportability reports and engineering details to assess quality of data prior to developing a readiness at cost model.
Document data gathering processes, pipeline configurations, and data flows to ensure consistency and future support.
Identify, define, and lead continuous improvement initiatives for analytics processes, data workflows, and system performance.
Ensure accuracy and completeness of all documentation.
Foster effective collaboration with cross-functional teams to achieve project objectives.
Communicate complex technical information clearly and effectively.
Utilize identified software and follow business rules and processes.
Identify areas to improve efficiency and accuracy and integrate those into modeling best practices.

Requirements

What you’ll need

Bachelor’s or Master’s degree in Engineering, Computer Science, Data Analytics, or a related technical field
Minimum of 10+ years of experience in systems engineering, logistics analysis, or modeling and simulation
Advanced experience in data engineering practices and readiness modeling methodologies within the DoD or equivalent complex enterprise environment
Expert in the application of reliability, maintainability, and availability (RMA) principles and lifecycle sustainment analysis
Lead multidisciplinary teams and coordinating across multiple stakeholders to deliver integrated technical solutions
Expert with Opus Suite (OPUS10, SIMLOX, CONNECT) or equivalent readiness-based sparing platforms
Strong communication, leadership, and analytical problem-solving skills.

Benefits

Comp & perks

Paid Time Off
Paid Company Holidays
Medical, Dental & Vision Insurance
Optional HSA and FSA
Base and Voluntary Life Insurance
Short Term & Long-Term Disability Insurance
401k Matching
Employee Assistance Program

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data analyticsstatistical modelingpredictive analysisdata engineeringreadiness modelingreliability principlesmaintainability principlesavailability principleslifecycle sustainment analysisdata pipeline architecture

Soft Skills

leadershipmentorshipcommunicationcollaborationanalytical problem-solvingprocess improvementtechnical expertisestakeholder engagementdocumentation accuracycross-functional teamwork