Digital Forensics Process Optimization Lead

Parsons; Maryland; Vor Ort; USD 88.000 - 155.000; Vollzeit

Zusammenfassung

Parsons is seeking a Digital Forensics Process Improvement Specialist to analyze CFL processes, identify bottlenecks, and develop data-driven recommendations to boost efficiency, quality, and performance across digital-forensics operations.

You will define and refine performance measures, develop trend analyses and workload projections, and collaborate with cross-functional teams to implement improvements and sustain accountability across CFL activities.

Qualifikationen

• Active Secret clearance required or equivalent.
• Eight years of process-improvement or related experience.
• Proven experience with digital-forensics techniques and processes.
• Ability to identify bottlenecks, delays, and control weaknesses and recommend improvements.

Aufgaben

• Identify bottlenecks, delays, duplicative activities, handoffs, rework, error sources, and control weaknesses across CFL processes.
• Develop corrective and preventive action recommendations.
• Propose standardization, automation, workflow redesign, improved data capture, and clearer roles and responsibilities.
• Collaborate with team to implement process improvements and measure performance.
• Define operational performance measures and develop trend analyses and workload projections.
• Evaluate results and suggest further optimization opportunities.
• Assist in creating process documentation, workflow maps, and performance reports.

Kenntnisse

Active Secret clearance

8+ years process-improvement

Digital-forensics knowledge

Data-driven decision making

Ausbildung

Bachelor's degree in Digital Forensics, Computer Science, Cybersecurity, IT, Criminal Justice, or related field

Jobbeschreibung

Parsons is seeking a Digital Forensics Process Improvement Specialist to analyze CFL processes, identify bottlenecks, and develop data-driven recommendations to boost efficiency, quality, and performance across digital-forensics operations.

You will define and refine performance measures, develop trend analyses and workload projections, and collaborate with cross-functional teams to implement improvements and sustain accountability across CFL activities.