Data Scientist

Overview:

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Responsibilities:

We are seeking a Data Scientist with strong industry experience to operate as a cross‑functional leader at the intersection of transportation operations, operations research, AI, and business strategy. This role partners deeply with Operations, Technology, Product, Finance, and Executive Leadership to design and deploy analytics and AI solutions that materially improve service reliability, efficiency, and decision‑making.

In addition to advanced modeling, this role serves as the enterprise champion for Agentic AI adoption, ensuring autonomous and semi‑autonomous systems are introduced responsibly, collaboratively, and with measurable operational impact.

Cross‑Functional Operating Model

This role does not sit in isolation within data science. Instead, you will:

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

You are expected to influence without authority and act as a unifying technical and strategic voice across functions.

Key Responsibilities

Transportation Operations & OR (Business‑Embedded)

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

Balance mathematical optimality with operational practicality and change management.

Agentic AI Champion (Enterprise‑Wide)

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

Establish shared standards for governance, observability, safety, and accountability of agentic AI across departments.

Microsoft Fabric & Cloud‑First Enablement

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

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.

Research‑to‑Operations Translation

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.

Produce internal frameworks, playbooks, and reference architectures used across teams.

Strategic Influence & Enablement

Serve as a trusted advisor to senior leaders on:

AI investment decisions

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.

Qualifications:

Required 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.

Agentic AI–Specific Requirements

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

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.

What Success Looks Like

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.

Where permissible under applicable state and local law, applicants may be subject to a pre-employment drug test and background check after receiving a conditional offer of employment.

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