Analytics & Decision Support Project-Program Director (Project-Program Director 6)

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health insurance

Dental and vision insurance

Life and disability insurance

401(k) matching

Job summary

Los Alamos National Laboratory seeks a visionary Analytics & Decision Support Project-Program Director to lead quantitative analytics for its billion-dollar infrastructure portfolio. You will guide AI/ML applications, portfolio optimization, risk analysis, and executive reporting to support strategic decisions at WIPO and federal program offices.

The role requires extensive experience in analytics platforms, dashboards, data governance, and stakeholder engagement, with a focus on mission

Qualifications

• Minimum of a bachelor's degree in a quantitative field and at least 15 years of relevant experience, or an equivalent combination.

Responsibilities

• Provide leadership for analytics and decision-support programs across the portfolio.
• Develop and deploy integrated tools for portfolio optimization and risk analysis.
• Apply AI/ML methods to infrastructure portfolio management and automated reporting.
• Create metrics, dashboards, and reporting systems for leadership and program offices.
• Lead scenario planning and capability alignment analyses with stakeholders.
• Coordinate with program directors to ensure analytics tools meet cross‑program needs.
• Establish data governance and standards across analytics systems.

Skills

Advanced analytics

AI/ML

Portfolio management

Executive communication

Stakeholder management

Education

Bachelor's degree in data science, CS, OR or related

Tools

Python

SQL

Tableau

Power BI

R

Job description

What You Will Do

The Weapons Infrastructure Program Office (WIPO) seeks a visionary leader to serve as the Analytics & Decision Support Project-Program Director. This Project-Program Director 6 position leads WIPO's analytic capabilities, providing the quantitative foundation for portfolio management, strategic planning, and executive decision-making across WIPO's billion-dollar infrastructure portfolio.

Responsibilities

• Strategic Analytics Leadership: Provide overall leadership, vision, and strategic direction for WIPO's Analytics & Decision Support Program, ensuring analytics capabilities enable data‑driven, transparent, and quantitative portfolio management across all WIPO program elements.
• Tool and System Development: Direct the development, deployment, and maintenance of integrated tools that quantitatively assess the WIPO portfolio, including portfolio optimization models, risk analysis frameworks, scenario planning systems, and decision support applications.
• Artificial Intelligence and Advanced Analytics: Lead the application of artificial intelligence, machine learning, and advanced analytical methods to infrastructure portfolio management, including predictive analytics for asset performance, optimization algorithms for resource allocation, and automated reporting and analysis capabilities.
• Metrics, Dashboards, and Reporting: Develop and maintain comprehensive metrics, dashboards, and reporting systems that provide transparent, accurate, and timely information on portfolio health, project performance, risk status, and mission capability readiness to WIPO leadership, Laboratory executives, and NNSA federal program offices.
• Scenario Planning and Strategic Analysis: Direct the development and application of scenario planning tools that capture, analyze, and communicate potential futures, enabling WIPO leadership to anticipate mission changes, evaluate alternative strategies, and make proactive portfolio decisions.
• Mission Capability Assessment: Develop and maintain quantitative frameworks for assessing infrastructure capability alignment with mission requirements, including gap analysis, capability forecasting, and investment prioritization models.
• Assurance and Effectiveness Evaluation: Lead the development of assurance and effectiveness evaluation frameworks that objectively assess WIPO program performance, identify improvement opportunities, and ensure continuous enhancement of portfolio management practices.
• Data Governance and Quality: Establish and enforce rigorous data governance standards, ensuring the highest levels of data accuracy, integrity, transparency, and security across all WIPO analytics systems and databases.
• NNSA Data Call Coordination: Serve as the primary point of contact for NNSA data calls, coordinating across WIPO program elements and Laboratory organizations to provide accurate, timely, and comprehensive responses to federal program office requests.
• Cross‑Program Integration: Coordinate closely with the other WIPO Program Directors (Capability Delivery, Transitions to Operations and Disposition, and Operations & Maintenance) to ensure analytics tools meet their needs and support integrated portfolio decision‑making.
• Laboratory Mission Assurance Integration: Interface with Laboratory mission assurance organizations, metrics and tool development groups, and data analytics teams to leverage institutional capabilities, avoid duplication, and ensure consistency with Laboratory‑wide data standards and governance.
• Federal Program Coordination: Interface with NA‑91, NA‑193, and other NNSA federal program offices to understand their data requirements, reporting expectations, and analytical needs, ensuring WIPO analytics capabilities support federal program management.
• Technical Innovation: Monitor external developments in program management analytics, data science, artificial intelligence, and decision support technologies, evaluating their potential applicability to WIPO portfolio management and leading implementation of beneficial innovations.
• Standards and Best Practices: Hold the Analytics & Decision Support Program element to the highest standards of accuracy, transparency, rigor, and professional excellence, implementing industry best practices and continuous improvement methodologies.
• Staff Leadership and Development: Lead, mentor, and develop a high‐performing team of data scientists, analysts, software developers, and decision support specialists, fostering a culture of innovation, rigor, and customer service.
• Executive Communication: Translate complex quantitative analyses into clear, concise insights and recommendations for WIPO leadership, Laboratory executives, and federal program managers, supporting high‑stakes decision‑making with rigorous analytical foundations.

Minimum Job Requirements

• Consultative‑level knowledge of advanced data analytics, data science, and quantitative decision support methodologies, including application to complex portfolio management, resource optimization, and strategic planning.
• Consultative‑level knowledge of artificial intelligence and machine learning technologies, including practical application to infrastructure management, predictive analytics, portfolio optimization, and automated decision support systems.
• Extensive experience developing, implementing, and maintaining enterprise‑level analytics platforms, dashboards, metrics systems, and reporting tools in complex organizational environments.
• Consultative‑level knowledge of scenario planning methodologies, risk analysis frameworks, and strategic forecasting techniques, including application to infrastructure portfolio management and mission capability planning.
• Extensive experience in data governance, data quality management, and establishing data standards across large, diverse organizations with multiple stakeholders and data sources.
• Consultative‑level knowledge of program and portfolio management principles, including project controls, earned value management, work breakdown structures, and performance measurement systems.
• Extensive experience interfacing successfully with senior executives, federal program managers, and diverse stakeholder groups, translating complex analytical findings into actionable insights and recommendations.
• Consultative‑level knowledge of DOE/NNSA program management requirements, including G2 or similar federal program management information systems, planning and budget process data requirements, and federal reporting expectations.
• Exceptional oral and written communication and presentation skills, including the ability to present complex quantitative analysis to non‑technical audiences and senior leadership.
• Extensive experience leading technical teams, including data scientists, software developers, and analysts, in matrixed organizational environments.
• Extensive experience leading organizational change, driving continuous improvement, and building high‑performing teams in matrixed, complex organizational environments.
• Ability to obtain a DOE Q clearance.

Desired Qualifications

• Consultative‑level knowledge of infrastructure lifecycle management, facility operations, construction project management, and asset portfolio management.
• Experience with the NNSA Weapons Complex, Nuclear Security Enterprise, and DOE/NNSA infrastructure programs, particularly NA‑91 and NA‑193.
• Deep understanding of the LANL weapons program, mission requirements, and infrastructure dependencies.
• Experience with cloud computing platforms, big data technologies, and modern software development practices (DevOps, Agile, CI/CD).
• Proficiency in multiple programming languages and analytical tools (Python, R, SQL, Tableau, Power BI, MicroStrategy, machine learning frameworks).
• Experience with optimization algorithms, operations research techniques, and mathematical modeling for portfolio management.
• Knowledge of DOE Orders, NNSA policies, Integrated Safety Management, and Laboratory procedures relevant to infrastructure management.
• Experience developing and implementing assurance and effectiveness evaluation frameworks for complex programs.
• Track record of innovation in analytics and decision support, including publications, patents, or recognition for technical contributions.
• Experience with mission assurance, risk management, and quality assurance in high‑consequence environments.
• An active DOE Q clearance.

Education and Experience

Position requires a minimum of a bachelor’s degree in data science, computer science, statistics, operations research, engineering, applied mathematics, or a related quantitative field, and at least fifteen years of relevant experience, or an equivalent combination of education and experience. An advanced degree (M.S. or Ph.D.) in a quantitative discipline is highly desired. Professional certifications in data science, analytics, or project management are preferred.

Work Environment

Work Location: Onsite in Los Alamos, NM. The work location is at the discretion of management.

Benefits: PPO or High Deductible medical insurance; Dental and vision insurance; Basic life and disability insurance; Paid childbirth and parental leave; Award‑winning 401(k) with 6% matching plus 3.5% annually; Learning opportunities and tuition assistance; Flexible schedules and time off (PTO and holidays); Onsite gyms and wellness programs; Extensive relocation packages (outside a 50‑mile radius).

Clearance

Q clearance is required. The selected applicant will be subject to a background investigation conducted by or on behalf of the Federal Government and must meet eligibility requirements for access to classified matter. The position requires a Q clearance, and obtaining such clearance requires U.S. citizenship except in extremely rare circumstances.

Equal Opportunity

Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations. The Laboratory is committed to making our workplace accessible to individuals with disabilities and will provide reasonable accommodations, upon request, for individuals to participate in the application and hiring process.