Principal Business Intelligence Lead, System Performance

Motional•Boston, MA

3d•$200,000 - $275,000

About The Position

Motional is seeking a Principal Business Intelligence Lead to own and elevate executive reporting on autonomous vehicle performance. The role translates complex robotics data, autonomy insights, and system performance metrics into strategic narratives for senior stakeholders. It will take immediate ownership of the weekly Software Performance Review (SPR) presented to leadership, including the CEO, and will develop the broader executive reporting ecosystem, commercial readiness reviews, and long-term autonomy trend analyses. The role partners with teams across autonomy, infrastructure, operations, and system performance to consolidate data into a cohesive release narrative. It also mentors junior engineers and advances team practices for data visualization and executive communication. The position will design automated reporting pipelines using AI workflows and integration frameworks to connect AV performance databases with presentation tools and reduce manual reporting work. The role may be hybrid, with in-office collaboration in Boston, Pittsburgh, or Las Vegas, or fully remote. The work environment regularly involves mechanical and computer parts, occasionally involves fumes and/or airborne particles, and has low-to-moderate noise. The stated base salary range is $200,000–$275,000 USD; additional compensation may include a bonus or company equity.

Requirements

At least 8 years of experience bridging business intelligence, data science, and strategic reporting in a complex technical field such as autonomous vehicles, robotics, or aerospace.
A master's degree in Business Analytics, Data Intelligence, or Robotics, or an MBA combined with a strong technical foundation in engineering problem spaces.
Excellent communication skills and experience leading executive presentations and high-visibility reviews.
Ability to use data to develop a compelling point of view, influence stakeholders, and drive actionable engineering decisions.
Ability to balance long-term system maturity strategy with detailed analysis of software release anomalies.
Strong foundational understanding of robotics systems, data architectures, and autonomous vehicle performance, perception, and prediction validation.
Expert judgment in selecting and designing visualizations that translate complex engineering outputs into clear executive-level insights.
Familiarity with AI-agent workflows and IDEs, such as Cursor or GitHub Copilot, and with API protocols such as MCP for securely connecting SaaS tools and databases.

Nice To Haves

Strategic management consulting experience in deep tech, AI, robotics, or automotive sectors.
Direct experience reporting on software readiness, simulation performance such as Software/Hardware-in-the-Loop, and autonomous systems safety metrics.
A track record of replacing manual presentation-building processes with scalable, code-driven slide-generation scripts.

Responsibilities

Analyze autonomous vehicle data pipelines, including heuristic extraction, diagnostic evaluations, and ETL-driven performance data, to identify and communicate the central insights.
Lead the weekly Software Performance Review and own leadership reporting on AV performance, calibrating metrics to executive goals and strategic questions.
Partner with leads across Heuristic Extractors, Reasoning Engine & Infrastructure, Diagnosis & Reporting, and Data & Metrics Analysis to unify data streams into a cohesive release narrative.
Mentor junior engineers and establish best practices for data visualization, chart design, and executive communication.
Architect and deploy automated reporting pipelines using AI workflows and integration frameworks such as Cursor IDE and MCP.
Connect AV performance databases to programmatic presentation tools, such as the Google Slides API, to generate weekly reporting decks and reduce manual reporting.
Develop the broader executive reporting ecosystem, commercial readiness reviews, and long-term autonomy trend analyses.