Director, Mobility Analytics, Strategy & Planning

About the Role

We're looking for a Director to lead the Customer Advocacy & Solutions’s Mobility engine that helps make and scale decisions. This leader owns the AI led analytical backbone, the strategic narrative, and the operating cadence that keeps a multi-billion-dollar business moving in the same direction.

You're joining at an inflection point. We're driving a transformation in our customer experience while growing at a rapid clip. The foundationals KPIs are changing and the very metrics that define "good" will shift underneath us as we move to an AI-first world at scale. This leader keeps the numbers trustworthy and comparable through that change, so the org can always tell real signals from a moving baseline.

We want a builder: someone who is AI-first by instinct, treats analytics, insights & planning as a scaled platform rather than a service desk, and can turn messy operational reality into clear, defensible strategy that executives act on. You'll partner closely with Product, Engineering, Operations, and Finance, and you'll be a trusted thought partner to senior leadership.

If you get energy from standing up systems that outlast any single project and you'd rather teach a model to answer a question than answer it manually a thousand times this role is for you.

This role is based in San Francisco and co-located with the leadership team. We believe the strategy, analytics, and planning function does its best work in close partnership — high-bandwidth, in the room, building together.

What You’ll Do

• Lead a multidisciplinary team spanning Analytics, Strategy, Planning, and Program Management, setting a high bar for rigor, speed, and clarity.
• Set the data integrity bar and enforce it. Establish data quality standards, lineage, SLAs, and alerting across Mobility's core datasets, so corruption and drift get caught before they hit eligibility, payouts, or decisions not after.
• Step-change time-to-root-cause. Build AI-assisted investigation automated anomaly detection, root-cause triage, and self-serve diagnostics that turns multi-day investigations into same-day (or same-hour) answers, and makes "why did this move?" a question the org can answer itself.
• Build scaled analytics platforms, not one-off reports. Design the data products, self-serve tooling, and AI-assisted workflows that let the broader org answer its own questions and move faster.
• Embed AI into how the team works. Champion an AI-first operating model using LLMs, agentic systems, and automation to compress cycle time on analysis, planning, and reporting, to detect and explain anomalies before they become escalations, and to surface insight that wouldn't scale through human effort alone.
• Own the strategic narrative for Mobility: translate data into a point of view, frame the tradeoffs for executives, and drive alignment on where we invest and why.
• Run the planning rhythm. Lead annual and quarterly planning, goal-setting, and the operating cadence that connects strategy to execution and holds the org accountable to outcomes.
• Drive cross-functional programs end to end — defining scope, sequencing the work, unblocking teams, and landing results across Product, Engineering, and Ops.
• Be a force multiplier for leadership, surfacing the signals that matter, pressure-testing decisions, and making sure the team is solving the right problems.

## What Good Looks Like

By the end of the first year, this leader should have moved the org to a place where:

• Investigations that used to take days take hours, and the path from "something's off" to "here's why" is largely self-serve in that time horizon.
• Leaders trust the numbers enough to act on them without re-checking because integrity, lineage, and monitoring are built in, not bolted on.
• AI and automation carry a meaningful share of the analysis, reporting, and anomaly detection proactively that used to consume the team's time.
• Strategy, planning, and execution run on one connected cadence, with a clear, defensible point of view on where Mobility invests and why.

Core Skills We’re Looking For

• Expertise in Data, Analytics & AI –Strong understanding of enterprise data platforms, analytics ecosystems, AI/ML workflows, and modern data architectures. Familiarity with agentic AI systems, LLM-powered applications, and emerging enterprise AI patterns is highly desirable.
• Trustworthy Data Foundations & Data Integrity – Proven track record of establishing data governance, quality standards, lineage, SLAs, and monitoring building data the org can defend under scrutiny, not just dashboards on top of unvetted inputs.
• AI-First Investigation & Automation – A clear vision — and hands-on experience — for using LLMs, automation, and agentic workflows to compress time-to-insight and time-to-root-cause, turning recurring manual investigation into scaled, self-serve capability.
• Stakeholder- & Customer-Facing Leadership Experience – Working directly with senior stakeholders and partner orgs (and, where relevant, external customers) to drive large-scale data transformation programs, solution architecture initiatives. Comfort engaging with executives, architects, engineers, analysts, and data scientists alike. Ability to connect technical strategy with measurable business impact.
• Product & Platform Mindset – Ability to identify recurring internal and customer challenges and translate them into scalable product feedback, platform requirements, and reusable solutions.
• Proven Cross-Functional Leadership – Track record of leading complex, cross-functional initiatives across Product, Engineering, Data, and partner organizations in fast-paced environments.
• Adaptability & Execution Velocity– Thrives in ambiguous, rapidly evolving environments. Demonstrates curiosity, ownership, and a bias toward action while navigating emerging technologies and shifting priorities.

Basic Qualifications

• 12+ years across analytics, strategy, planning, & program management, with significant time leading teams.
• A strong track record of building and scaling analytics or data platforms into systems and tooling, not just deliverables.
• Demonstrated AI-first fluency: hands-on experience applying LLMs, automation, or ML to scale analysis and decision-making.

Preferred Qualifications

• Experience in marketplace, mobility, logistics, or other high-scale operational businesses.
• Background spanning both strategy and execution — equally credible setting direction and running the program that delivers it.
• Technical depth (SQL, Python, modern data stack, modeling) sufficient to lead analytics and AI teams with credibility.

For San Francisco, CA-based roles: The base salary range for this role is USD$239,000 per year - USD$265,500 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits).

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.