Director, Analytics and Reporting

Director, Analytics and Reporting

Department: Data Location: Austin, TX Reports to: SVP, Data

The Opportunity

Stealth Startup is a technology company with a public safety mission. Through relentless innovation and discovery, we are strengthening trust, safety, and transparency across the student transportation space and making the trip to and from school safer for students.

Within this mission, the Director, Analytics and Reporting will lead our Analytics & Reporting function — a team responsible for turning data into decisions across Stealth Startup. This role sits at the intersection of strategy, execution, and enablement : you will own a portfolio of KPIs, dashboards, and analytical products, while also shaping how Stealth Startup uses data to manage performance, run experiments, and make tradeoffs.

You will:

• Lead and grow the Analytics & Reporting team, setting the vision, standards, and operating model for how we perform analytics and build data products at Stealth Startup.
• Own the end-to-end analytics and reporting portfolio: core KPI frameworks, dashboard and reporting strategy, and the roadmap for data insight tools (e.g., Tableau, enterprise scorecards, internal apps) — and partner with the AI tooling owner to thoughtfully integrate AI into analytics and report generation.
• Stay hands-on with high-impact analyses, dashboard design, and metric definition, especially for the most critical or ambiguous questions.

This is a highly visible role that will work closely with executive stakeholders, journey leads, and the broader Data and Product/Tech organizations.

Key Responsibilities

1. Strategy, Ownership, and Stakeholder Partnership

• Set and continually refine the overall analytics strategy and data visualization approach for the Analytics & Reporting team, including KPI frameworks, dashboard design standards, and how insights are presented to different audiences.
• Partner with project management to translate company and departmental priorities into a focused analytics roadmap : metrics to define, dashboards to build, experiments to run, and tools to improve.
• Partner with senior stakeholders (e.g., Operations, Product, GovOps, Fleet Ops, Finance, Sales/Marketing) to:
• Clarify business questions and decision points.
• Align on success metrics and definitions.
• Prioritize work based on impact and urgency.
• Act as the “voice of data” in forums such as MBRs and strategic planning sessions, bringing clear narratives, tradeoffs, and recommendations — not just charts.

2. Team Leadership and People Management

• Directly manage a team of Data Analysts and Senior Data Analysts across onshore and offshore locations (and, over time, additional analytics roles).
• Build a high-performing, product-minded analytics team that:
• Understands the business deeply.
• Asks good questions and challenges assumptions.
• Designs analyses, dashboards, and other data products that are genuinely useful to end users.
• Define clear roles, responsibilities, and ways of working within the Analytics & Reporting function and with partner teams (Data Engineering, Data Science, Product, Operations, Finance, etc.).
• Coach and develop team members on:
• Analytical rigor and methodology.
• Stakeholder management and storytelling.
• Project scoping, estimation, and prioritization.
• Foster a culture of continuous improvement, shared learning, and psychological safety — where the team can ship, get feedback, and iterate quickly.

3. Hands-On Analytics and Reporting

While this is a leadership role, it is expected to remain hands-on :

• Serve as the primary analytics owner for one or more departments and/or journey teams, ensuring that leaders have the data and insights they need to run the business.
• Own the design and build of high-impact dashboards and reports (e.g., enterprise scorecards, operational performance views, funnel metrics, safety impact analyses).
• Lead complex or ambiguous analyses end-to-end: from problem framing and data discovery, through modeling and visualization, to recommendations and follow-through.
• Partner closely with Data Engineering to:
• Define data requirements and model structures that support your team’s work.
• Ensure data quality, lineage awareness, and documentation (in collaboration with governance tooling like Atlan).
• Establish and maintain standard reporting packages for your domains (e.g., weekly operational views, monthly business reviews, quarterly strategic reviews), including clear owner, cadence, and intended decisions.

4. Metrics, Experimentation, and Performance Management

• Help to define and maintain metric catalogues for your domains:
• Primary KPIs, supporting diagnostics, and derived metrics.
• Clear definitions, calculation logic, and associated business context.
• Partner with Product, Operations, and Data Science to:
• Design and analyze experiments (A/B tests, pilots, controlled rollouts) where applicable.
• Build repeatable methods for measuring impact of new features, process changes, or programs.
• Work with department leaders to ensure that metrics are actually used in decision-making and performance management — not just published.

5. Process, Tooling, and Self-Service Enablement

• Collaborate with the SVP of Data, Data Engineering leadership, and AI leadership to scale self-service analytics , including:
• Designing “good enough” self-serve experiences for technically minded business users.
• Establishing governance and guardrails around metric definitions and production dashboards.
• Contribute to the evolution of our analytics stack (e.g., Redshift, Tableau, internal tools, AI copilots such as PatrolIQ) by providing requirements, feedback, and design input.
• Continuously refine how analytics work flows from intake → triage → execution → validation → operationalization, leveraging tools like Jira and shared documentation.

Qualifications

Must-Have

• 8+ years of experience in analytics, business intelligence, or closely related roles, with at least 3+ years leading analysts (people management and/or strong team leadership in a matrixed environment).
• Proven track record building and maintaining production-grade dashboards and reports that support executive and operational decision-making.
• Strong proficiency in:
• SQL for data extraction, transformation, and modeling.
• At least one analytical language (e.g., Python or R) for deeper analysis and automation.
• Modern BI / visualization tools (e.g., Tableau or similar).
• Demonstrated ability to:
• Partner with senior stakeholders to frame questions and make tradeoffs.
• Tell clear, concise stories with data, tailored to different audiences (executives vs. operators vs. technical teams).
• Lead cross-functional efforts where analytics is one of several workstreams.
• Experience working with data engineering teams and familiarity with modern data platforms such as Redshift, S3, and Glue/ETL.

Nice-to-Have

• Experience in operations-heavy or B2G / public safety environments, where process, compliance, and outcomes all matter.
• Experience leading distributed and/or offshore analytics teams and managing handoffs across time zones.
• Experience leading distributed and/or offshore analytics teams and managing handoffs across time zones.
• Prior ownership of analytics for one or more of:
• Customer success / support / GovOps.
• Fleet / field operations.
• Revenue operations, Sales, or Marketing.
• Familiarity with data governance and metric catalog tools (e.g., Atlan) and practices.
• Exposure to data science / ML concepts, especially around experimentation, forecasting, or anomaly detection (direct hands-on modeling is a plus but not required).
• Experience working with or around GenAI tools and copilots, especially for analytics and reporting workflows.