Transit Performance and Reporting Analyst

Ryan Mahoney

Why this role is hard · Ryan Mahoney

The hardest part is finding someone who cares more about accurate data than being right. You need an analyst who can tell an operations manager their on-time performance numbers are wrong without starting an argument. They have to check the data pipeline themselves and then explain the issue to a leader who isn't technical. Most applicants can write the query, but few stand by the result when things get heated.

Core Evaluation

Critical questions for this role

The competency and attitude questions below are where the hiring decision is made. They run in the live interview rounds and are calibrated to the level selected above.

19 Competency Questions

1 of 19

  1. Discipline

    Data Engineering & Governance

  2. Job requirement

    Data Architecture & Storage

    Optimizes database schemas and manages storage costs.

  3. Expected at Mid

    Schema optimization supports efficiency goals but major architectural decisions are reserved for senior staff; mid-level analysts apply guided improvements to enhance query performance and manage storage costs.

Interview round: Cross-Functional Stakeholder Collaboration

Recall a project where you structured storage for historical data that was rarely accessed.

Positive indicators

  • Considers cost implications of storage
  • Maintains data integrity during archiving
  • Documents retention and access methods

Negative indicators

  • Deletes data to save space without policy
  • Stores everything on expensive high-performance storage
  • No plan for retrieving archived data

15 Attitude Questions

1 of 15

Accountability Mindset

The consistent willingness to accept responsibility for outcomes, data accuracy, and reporting integrity, regardless of external factors, while actively seeking solutions to rectify discrepancies and maintain stakeholder trust.

Interview round: Hiring Manager Technical & Domain

How do you manage your workflow when multiple regulatory deadlines converge?

Positive indicators

  • Uses tracking tools
  • Flags risks
  • Negotiates timeline

Negative indicators

  • Misses deadlines
  • Sacrifices quality
  • Works in silence

Supporting Evaluation

How candidates earn the selection conversation

The goal is to reduce effort for everyone by collecting more useful signal before adding more interviews. Lightweight application prompts and structured screens help the panel focus live time on the candidates most likely to succeed.

Stage 1 · Application

Filter at the door

Runs the moment a candidate hits Submit. Disqualifying answers end the application; everything else is captured for review.

Knock-out Questions

1 of 2

Application Screen: Knock-out

Have you directly prepared or audited federal transit compliance reports, such as NTD submissions, FTA safety metrics, or Title VI equity audits?

Yes
Qualifies
No
Auto-decline

Video-Response Questions

1 of 2

Application Screen: Video Response

Imagine you are preparing the monthly Board Performance Report and discover that on-time performance metrics have dropped significantly due to legacy AVL sensor errors rather than actual service issues. How would you present this finding to non-technical board members while ensuring they understand the data reliability constraints and the corrective steps you're taking?

Candidate experience

REC
0:42 / 2:00
1Record
2Review
3Submit

Response time

2 min

Format

Recorded video

Stage 2 · Resume Screening

Read the resume against fixed criteria

Reviewers score every application that clears the door against the same criteria. Stronger reviews advance to live interviews; weaker ones are archived without further screening.

Resume Review Criteria

8 criteria
Independently troubleshooting data flow issues, debugging scripts, and implementing standard fixes to ensure reliable performance reporting.
Designing and maintaining performance dashboards that translate query results into actionable service reliability insights for operations managers.
Independently preparing federal transit submissions and reconciling automated fare collection data against financial records.
Collaborating with operations, finance, or planning teams to align data collection practices with reporting requirements and resolve metric discrepancies.

Does the cover letter or personal statement convey clear relevance and familiarity with the job?

Does the resume indicate required academic credentials, relevant certifications, or necessary training?

Is the resume complete, well-organized, and free from formatting, spelling, and grammar mistakes?

Does the resume show relevant prior work experience?

Stage 3 · During Interviews

Where the hire is decided

Interview rounds use the competency and attitude questions outlined above, then add tests, work simulations, and presentations that reveal deeper evidence about how the candidate thinks and works.

Presentation Prompt

Prepare a short deck walking us through a past project where you defined a new performance metric or refined an existing one. Discuss how you aligned the metric definition with operational managers, handled pushback or conflicting interpretations, and ensured the final metric drove actionable service changes. Focus on your reasoning, tradeoffs, and how you managed stakeholder expectations.

Format

deck-and-walkthrough · 20 min · ~2 hr prep

Audience

Performance reporting leadership and cross-functional operations partners.

What to prepare

  • 3-5 slides summarizing the context, your approach to metric definition, stakeholder alignment process, and outcomes.

Deliverables

  • A 3-5 slide deck and a structured verbal walkthrough of your methodology and stakeholder engagement.

Ground rules

  • Redact any confidential or proprietary data from your slides.
  • Focus on your decision-making process and communication strategy rather than raw numbers.
  • Do not build new strategic artifacts; use a real past project or anonymized equivalent.

Scoring anchors

Exceeds
Presents a compelling narrative that bridges technical metric design with operational impact, explicitly detailing how conflicting stakeholder inputs were reconciled into a unified, actionable standard.
Meets
Clearly explains the metric definition process, shows evidence of stakeholder consultation, and links the metric to operational adjustments.
Below
Focuses only on the technical calculation without addressing operational alignment, ignores stakeholder dynamics, or fails to demonstrate how the metric improved decision-making.

Response time

20 min

Positive indicators

  • Clearly articulates the business problem the metric was meant to solve
  • Describes specific techniques used to align technical definitions with operational reality
  • Acknowledges tradeoffs in metric precision versus usability
  • Demonstrates how feedback was incorporated into the final definition

Negative indicators

  • Presents the metric without explaining the underlying operational context
  • Ignores stakeholder pushback or frames it as purely technical
  • Fails to connect the metric to actionable service changes
  • Uses excessive jargon without translating it for operational audiences

Work Simulation Scenario

Scenario. You own the monthly route efficiency reporting module. The Operations Manager has requested a 1:1 meeting to discuss a recent 12% dip in on-time performance for the downtown express routes. They are asking you to 'smooth out' the metric by excluding a week of heavy rain and road closures, arguing it skews the monthly average and misrepresents driver performance.

Problem to solve. Drive the conversation with the Operations Manager. Balance their desire for a favorable performance narrative with your obligation to maintain accurate, auditable safety and service data. Decide how to present the metrics transparently while acknowledging legitimate external factors.

Format

stakeholder-roleplay · 35 min · ~1.5 hr prep

Success criteria

  • Maintain data integrity and compliance standards without being adversarial
  • Acknowledge operational context while explaining why selective exclusion violates reporting policy
  • Co-create a presentation approach that contextualizes the dip rather than hiding it

What to review beforehand

  • Agency policy on data exclusion and regulatory reporting standards
  • Best practices for contextualizing performance metrics in operational reviews

Ground rules

  • This is a live 1:1 conversation, not a written assignment
  • Focus on your communication, boundary-setting, and problem-solving approach
  • You will not be asked to produce a slide deck or revised report during the simulation

Roles in scenario

Operations Manager (skeptical_stakeholder, played by cross_functional)

Motivation. Wants to protect driver morale and avoid negative scrutiny from executive leadership over a temporary weather-related disruption.

Constraints

  • Under pressure from regional leadership to show consistent performance improvements
  • Cannot override federal or state reporting compliance requirements
  • Needs actionable insights, not just raw negative numbers, to justify schedule adjustments

Tensions to introduce

  • Push back gently on the idea that the data tells the 'whole story'
  • Emphasize that drivers are being unfairly penalized in internal reviews
  • Ask for a compromise that acknowledges the anomaly without breaking reporting rules

In-character guidance

  • Express frustration professionally but remain open to collaborative solutions
  • Acknowledge when the candidate explains compliance constraints clearly
  • Shift focus to how the data can be framed constructively if the candidate offers a path forward

Do not

  • Do not escalate hostility or make unreasonable demands
  • Do not concede immediately; require the candidate to articulate a compliant framing
  • Do not solve the reporting problem for the candidate

Scoring anchors

Exceeds
Firmly upholds compliance boundaries while actively partnering with operations to reframe the narrative constructively, resulting in a mutually acceptable, transparent reporting approach.
Meets
Maintains data integrity standards, explains compliance constraints clearly, and proposes a basic alternative for contextualizing the performance dip.
Below
Yields to pressure to alter data, becomes defensive, or fails to provide a compliant and actionable alternative for presenting the metrics.

Response time

35 min

Positive indicators

  • Clearly explains why selective data exclusion violates compliance and audit standards
  • Listens actively to operational concerns and validates legitimate external factors
  • Proposes a transparent alternative (e.g., supplemental notes, segmented reporting, or anomaly flags)
  • Maintains a collaborative tone while firmly protecting data integrity

Negative indicators

  • Agrees to alter or exclude data without pushing back on compliance requirements
  • Uses defensive or dismissive language when challenged by the manager
  • Fails to offer a constructive framing or alternative presentation strategy
  • Overuses technical jargon without translating it into operational impact

Progression Framework

This table shows how competencies evolve across experience levels. Each cell shows competency at that level.

Data Engineering & Governance

5 competencies

CompetencyJuniorMidSeniorPrincipal
Data Architecture & Storage

Utilizes existing storage structures and queries data.

Optimizes database schemas and manages storage costs.

Designs data warehouse architectures and migration strategies.

Defines long-term data architecture vision and technology stack.

Data Governance & Security

Follows established governance protocols and access requests.

Manages user access roles and audits data usage.

Develops governance policies and ensures regulatory compliance.

Defines enterprise data governance framework and risk strategy.

Data Quality Assurance

Executes predefined data quality checks and reports anomalies.

Designs validation routines and troubleshoots data quality issues independently.

Establishes data quality standards and leads root cause analysis for systemic issues.

Defines organizational data quality strategy and integrates quality into architecture.

ETL Pipeline Management

Monitors existing ETL jobs and handles basic failures.

Develops new pipeline components and optimizes existing workflows.

Architects scalable ETL solutions and manages complex dependencies.

Sets standards for data ingestion and oversees enterprise pipeline strategy.

Regulatory Compliance & Audit

Collects data for compliance reports under supervision.

Prepares standard compliance submissions and maintains audit trails.

Interprets regulatory changes and adjusts reporting frameworks.

Leads regulatory strategy and represents organization in audits.

Performance & Business Intelligence

5 competencies

CompetencyJuniorMidSeniorPrincipal
Executive Reporting & Communication

Drafts sections of reports and validates data accuracy.

Presents findings to internal teams and manages report distribution.

Presents to executives and translates technical findings for business audiences.

Shapes communication strategy and represents analytics function externally.

Operational Data Analysis

Performs descriptive analysis on provided datasets.

Conducts diagnostic analysis and recommends operational changes.

Leads complex analytical projects and mentors junior analysts.

Directs analytical agenda and integrates insights into operations.

Performance Metric Definition

Calculates standard KPIs using defined formulas.

Refines metric definitions and identifies data sources for new KPIs.

Aligns KPIs with operational goals and validates metric accuracy.

Defines enterprise performance framework and strategic metrics.

Predictive Modeling & Forecasting

Runs existing forecasting models and validates outputs.

Develops regression models and tunes forecasting parameters.

Designs predictive models and integrates machine learning techniques.

Establishes modeling standards and oversees AI/ML strategy.

Strategic Reporting & Alignment

Assists in compiling data for strategic decks.

Creates regular strategic reports and presents to management.

Interprets data for strategic decisions and advises leadership.

Defines reporting strategy and drives organizational alignment.