The Efficiency Lead is responsible for designing, implementing, and overseeing the contract’s quality assurance (QA), quality control (QC), continuous improvement, and risk management processes. This role ensures all deliverables, analytic products, and operational processes consistently meet or exceed ODNI, NCTC, and IC standards for accuracy, timeliness, compliance, and efficiency. The Lead will drive a culture of excellence by leveraging automation, artificial intelligence (AI), and advanced technology solutions to optimize workflows, enhance data-driven decision-making, and streamline operations across all contract functions. The Lead is expected to proactively identify and implement technology-enabled process improvements, risk management strategies, and quality control measures to support the NCTC mission and foster continuous organizational advancement.

Key Responsibilities

Quality Assurance

• Collaboration:
  Work closely with the Program Manager, Task Leads, and Government counterparts to ensure alignment of CPI and Risk initiatives with evolving mission priorities, utilizing technology-enabled collaboration and workflow tools where appropriate

• Quality Management System (QMS):

  • Develop a center-wide QMS that includes Continuous Process Improvement (CPI), Risk Management, and Quality Control (each detailed below),incorporating automation and digital tracking where feasible.

  • Develop, implement, and maintain a comprehensive Quality Management Plan (QMP) in accordance with contract requirements, ODNI/NCTC policies, and IC analytic tradecraft standards, leveraging data analytics and AI-driven insights to inform quality strategies.

• Compliance Oversight:
  Ensure all contract activities adhere to applicable laws, policies, and standards (including data integrity, privacy, and security requirements). Prepare for and support internal and external audits, utilizing automated compliance monitoring tools where possible

• Performance Metrics:
  Define, track, and report on key performance indicators (KPIs), Service Level Agreements (SLAs), and quality metrics, using automated dashboards and data visualization tools to enable real-time monitoring and reporting . Analyze trends and recommend corrective actions as needed, supported by AI-driven analytics.

• Reporting:
  Prepare and present regular quality and efficiency reports to contract leadership and Government stakeholders leveraging automated reporting solutions to streamline the process. Support the preparation of status reports (MSR, TSM) and QMP updates.

Continuous Process Improvement (CPI)

• Strategic Positioning:

• Facilitate strategic positioning assessments (using tools such as SWOT, SOAR, NOISE) with program leadership to assess the alignment of resources to program needs, gaps in performance, and identify emerging risks and opportunities, utilizing digital assessment and visualization tools.

• Ensure new risks identified are processed via the Risk Management process, as appropriate, with the support of automated risk tracking systems.

• Collect CPI Inputs:
  Solicit internal and external feedback, evaluate award fee reports and customer comments, monitor risks, conduct root cause analyses of issues, and collect lessons learned and opportunities for improvement from all levels of staff across all task areas to support robust CPI. Employ AI-enabled survey and feedback tools and document review to enhance data collection and analysis speed and accuracy.

• Identify CPIs: Identify Potential CPI tasks. Quantify the resources required and potential impact of each using data analytics and process modeling tools.

• Support CPI Prioritization: Regularly brief program leadership on the Potential CPI List for disposition (accept/reject) resource allocation, and prioritization leveraging digital workflow and prioritization tools.

• Process Improvement:

  • Following program leadership prioritization and resource allocation, design and lead initiatives to improve operational efficiency, reduce error rates, and streamline workflows across analytic, operational, and support functions, with a focus on automation and AI-driven process optimization.

  • Collect baseline and post-implementation performance measures to provide quantitative evidence of improvements achieved, using automated data collection and analytics platforms.

Risk Management

• Risk Management:

  • Design and execute a Risk Management framework that includes the identification, assignment, impact and severity scoring (pre and post mitigation), and monitoring of risks over their lifecycle.

  • Facilitate regular risk review meetings with program leadership, and regular risk identification and collection from all staff using digital collaboration and risk tracking platforms.

  • Support external risk reporting in CDRLs (MSR, TSM, etc.) utilizing automated reporting tools.

  • Ensure risks and their mitigations are considered for CPI inclusion, supported by integrated risk and process improvement tracking systems.

Quality Control (QC)

• QC Processes: Oversee the development of Task-area QC Processes (within operational control),incorporating automation and digital QC tools where appropriate.

• Product Review:

  • Document Leidos review processes for delivered products (center-wide CDRLs and Task specific) and validate their effectiveness, using digital documentation and workflow management tools.

  • Oversee the review and evaluation of analytic and operational products for accuracy, completeness, and compliance with IC tradecraft standards, leveraging AI-enabled review and validation tools.

  • Develop monitoring methods and measures that will provide leading indication of degrading product quality, using predictive analytics and automated monitoring solutions.

  • Provide feedback and coaching to staff.

• Performance Metrics: Support the collection and analysis of the metrics (KPI, SLA, quality metrics) defined in the Quality Assurance approach using automated data collection and analytics tools.

Required Qualifications

• Bachelor’s degree in a relevant field (e.g., Intelligence, Engineering, Quality Management, Business, or related discipline); Master’s preferred.

• 7+ years of experience in quality assurance, process improvement, or analytic tradecraft in a national security, intelligence, or government contracting environment.

• Demonstrated experience developing and managing QA/QC programs and continuous improvement initiatives, including the use of automation, AI, and technology to drive efficiency and optimize processes.

• Demonstrated experience in risk management, preferably in a dynamic environment/rapidly evolving operating landscape.

• Proven ability to define, track, and analyze performance metrics, SLAs, and quality indicators using analytics, automated dashboards, and reporting tools.

• Experience with digital collaboration platforms, workflow management, and technology-enabled communication and facilitation.

• Strong analytical and problem-solving skills, with a track record of leveraging data and technology to inform decision-making and corrective actions.

• Ability to work in a fast-paced, high-stakes, and classified environment.

• Active TS/SCI clearance with CI Polygraph (Full Scope Poly preferred).

Preferred Qualifications

• Experience with analytic automation, AI/ML, or data science quality programs, including the implementation of AI-enabled review, validation, and risk management solutions.

• Strong knowledge of IC analytic tradecraft standards, ODNI/NCTC policies, and federal compliance requirements.

• Six Sigma, Lean, or similar process improvement certification, with demonstrated experience applying these methodologies using digital and automated tools.

• Experience supporting ODNI, NCTC, or other IC agencies.

• Experience on large scale staffing or staff augmentation programs with significant surge and scale dynamics.

• Professional certification in instructional design, adult learning, or training management, with experience in technology-enabled training delivery.

• Full Scope Poly preferred

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.