Role overview
If you reside in California, please see our California Applicant Privacy Policy for more information about our data handling practices and your data rights.
Responsibilities
- Co‑create solutions with Operations and Planning leaders
- Partner with IT, Data Engineering, and Platform teams on scalable cloud architectures
- Collaborate with Product and Innovation teams on user‑centric decision tools
- Engage Finance and Procurement on cost, ROI, and optimization tradeoffs
- Advise Executive Leadership on AI strategy, automation risk, and operational impact
- Work directly with operations, dispatch, and planning teams to understand constraints, tradeoffs, and real‑world decision processes.
- Design and deploy operations research and analytics solutions for:
- + Scheduling and rostering Fleet sizing and allocation Demand forecasting and capacity planning Service reliability, on‑time performance, and cost optimization
- Fleet sizing and allocation
- Demand forecasting and capacity planning
- Service reliability, on‑time performance, and cost optimization
- Balance mathematical optimality with operational practicality and change management.
- Act as the cross‑functional champion for Agentic AI, driving alignment across technical, operational, and leadership teams.
- Identify opportunities where agent‑based systems can augment planners, dispatchers, analysts, and executives.
- Design agentic workflows that integrate:
- + Planning and reasoning Optimization tools and simulation engines Data platforms, APIs, and business rules Human‑in‑the‑loop controls for safety‑critical decisions
- Optimization tools and simulation engines
- Data platforms, APIs, and business rules
- Human‑in‑the‑loop controls for safety‑critical decisions
- Establish shared standards for governance, observability, safety, and accountability of agentic AI across departments.
- Partner with data engineering and platform teams to deliver solutions on Microsoft Fabric, including:
- + OneLake, Lakehouses, and Warehouses Fabric Notebooks (Python / Spark) Power BI semantic models for operational decision support
- Fabric Notebooks (Python / Spark)
- Power BI semantic models for operational decision support
- Ensure analytics and AI outputs are consumable by both technical and non‑technical users.
- Influence cloud architecture decisions to support real‑time and large‑scale transportation analytics.
- Bring PhD‑level rigor into applied, cross‑functional problem solving.
- Translate advances in:
- + Operations research Machine learning Reinforcement learning Agentic and autonomous systems into solutions that can be operationalized and sustained.
- Machine learning
- Reinforcement learning
- Agentic and autonomous systems into solutions that can be operationalized and sustained.
- Produce internal frameworks, playbooks, and reference architectures used across teams.
- Serve as a trusted advisor to senior leaders on:
- + AI investment decisions Automation risk and readiness Tradeoffs between cost, service quality, and equity
- Automation risk and readiness
- Tradeoffs between cost, service quality, and equity
- Mentor data scientists, analysts, engineers, and operations staff to raise AI literacy across the organization.
- Facilitate cross‑functional forums or working groups around analytics, AI, and automation.
Basic qualifications
- Masters/PhD in Operations Research, Industrial Engineering, Transportation Engineering, Computer Science, Applied Mathematics, Statistics, or a related field.
- 7+ years of industry experience working in transportation, logistics, mobility, or complex operational environments.
- Demonstrated success operating in highly cross‑functional settings.
- Deep expertise in optimization, simulation, and statistical modeling, combined with ML.
- Strong programming skills in Python; experience integrating OR solvers and dashboards.
- Experience delivering solutions in cloud‑based, enterprise environments.
- Exceptional communication and stakeholder‑management skills.
- Experience leading or designing agentic AI systems across multiple teams or functions.
- Ability to explain agentic concepts clearly to operations, leadership, IT, and risk teams.
- Strong judgment in distinguishing when:
- + Deterministic OR is sufficient ML adds value Agentic AI is appropriate
- ML adds value
- Agentic AI is appropriate
- Commitment to responsible AI deployment, particularly in safety‑, equity‑, and compliance‑sensitive transportation systems.
Preferred qualifications
- Experience in public transit, paratransit, logistics, or large fleet operations.
- Familiarity with Microsoft Azure and Fabric‑based analytics ecosystems.
- Experience influencing AI governance, operating models, or centers of excellence.
- Prior leadership in enterprise transformation or modernization initiatives.
- Operations trust and actively use analytics and AI solutions.
- Agentic AI is adopted intentionally, safely, and cross‑functionally—not in silos.
- Microsoft Fabric enables shared, consistent decision‑making across teams.
- Leadership views this role as a connector between strategy, technology, and day‑to‑day operations.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Data Science Robotics