Supervisor of Engineering Analytics & Modeling

We seek a builder of technical engineering organizations

We are seeking a forward-thinking leader who will help us continue building and maturing Engineering Analytics & Modeling, developing engineering leaders, strengthening talent practices, establishing strategic direction, and forging the enterprise relationships necessary to convert emerging technical work into sustainable business capabilities. This is not a role centered on individual technical contributions. It is a frontline leadership position for seasoned technical leaders who can guide experts, quickly learn complex concepts, make sound decisions amid ambiguity, and help a multidisciplinary organization deliver measurable business impact.

Job Summary: Lead the Next Stage of Engineering Analytics & Modeling

The Supervisor of Engineering Analytics & Modeling will lead the organization responsible for Electric Transmission forecasting and Measurement Analysis & Modeling. The portfolio includes forecast product development and delivery, scenario and medium-horizon methods, high-resolution telemetry and synchrophasor analysis, measurement-informed model validation, modeling and simulation, and applied R&D. The team operates where methods and industry practices are still forming. Success requires a leader who can see one to three years ahead, preserve the team’s ability to innovate, and establish the structure, accountability, and stakeholder confidence needed for these capabilities to mature inside a large, regulated enterprise.

Job Summary

• Set direction and mature capabilities: Establish strategy, priorities, roadmaps, and operating practices that move Forecasting and Measurement Analysis & Modeling from emerging work into trusted, repeatable services.
• Lead and develop a multidisciplinary team: Coach, challenge, and align engineers, data scientists, modelers, signal-processing specialists, project leaders, and supporting technical resources. Lead a team that includes highly accomplished professionals with advanced academic credentials and recognized influence within the power utility industry, while creating clear expectations and meaningful development paths that foster technical excellence, collaboration, and continued professional growth.
• Connect strategy to execution: Translate one-to-three-year objectives into executable portfolios, resource plans, decision points, delivery commitments, and measures of business impact.
• Advance forecasting: Guide development of transparent, explainable, reproducible, and scenario-based forecasting capabilities that support operations, planning, capital strategy, and other business decisions.
• Mature our measurement analysis and modeling capabilities: Guide high-resolution telemetry analysis, grid-dynamics research, model validation and calibration, simulation, and measurement-informed engineering review.
• Create technical accountability: Promote rigorous review of assumptions, methods, failures, findings, and next steps, so research produces reusable learning, stronger decisions, and durable capabilities.
• Navigate and influence the enterprise: Build productive relationships across engineering, operations, planning, technology, data, vendors, and leadership to resolve organizational barriers and earn adoption for new approaches. Translate complex engineering and analytical concepts into clear, actionable insights for executive leadership and other stakeholders, enabling informed decision-making and organizational alignment.
• Manage the organization: Own performance management, work prioritization, staffing, recruiting, onboarding, succession, training, resource allocation, risk escalation, and day-to-day supervisory responsibilities.

Required Knowledge, Skills, Abilities & Experience

• Experience: Minimum seven (7) years of progressively responsible experience in engineering, technology, analytics, research, project or program leadership, or a closely related technical field.
• Technical-team leadership: Demonstrated experience leading teams or major initiatives that innovate in engineering, technology, analytics, research, or a parallel technical discipline. Engineering leadership, project leadership, and program leadership will be considered viable evidence.
• Organizational building and impact: Demonstrated history of building, growing, maturing, scaling, or transforming a technical team, program, or capability, supported by specific examples of measurable organizational or business impact.
• Leadership through ambiguity: Ability to create clarity, make decisions with incomplete information, adapt to changing priorities, and convert uncertain or evolving needs into coordinated action.
• Strategic perspective: Ability to identify capability gaps, anticipate future needs, establish a one-to-three-year direction, and balance long-term development with current delivery obligations.
• Multidisciplinary leadership and technical learning: Ability to lead specialists across multiple domains and rapidly learn enough technical context to test assumptions, ask consequential questions, assess risk, and guide sound decisions without needing to be the deepest subject-matter expert.
• Talent leadership: Demonstrated ability to coach, develop, motivate, and hold technical professionals accountable while building a healthy, candid, and high-performing culture.
• Enterprise influence and communication: Ability to translate technical complexity into clear business choices and influence outcomes across organizational boundaries, including technical, operational, and executive stakeholders.

Preferred Qualifications

• Formal leadership: Prior supervisory or management experience, including responsibility for performance, staffing, talent development, and organizational outcomes.
• Emerging capability leadership: Experience leading an innovation, advanced analytics, applied R&D, product, startup-style, or other technical organization where the playbook was incomplete and the team had to establish new practices while delivering results.
• Relevant technical environment: Experience with engineering analytics, forecasting, time-series data, data science, signal processing, high-resolution telemetry, power systems, modeling and simulation, or model validation and calibration.
• Large-enterprise execution: Experience maturing innovative work within a large, regulated, safety-critical, or operationally complex enterprise, including effective partnership with technology and governance organizations.

Education Requirements

Bachelor’s degree in engineering, computer science, data science, mathematics, statistics, technology management, or a related discipline is preferred. Equivalent experience leading complex technical organizations or maturing emerging capabilities should be considered where appropriate. Advanced degrees, professional credentials, and formal project, program, product, or agile leadership experience are valued but not required.

Licenses, Certifications, or Quals Description

None required

Working Conditions

Other Working Conditions

Test Description