Product Manager, Data Review

Nominal•Los Angeles, CA

About The Position

Nominal is building the connected test and operations platform powering the world's most advanced hardware systems, from spacecraft and autonomous vehicles to next-generation defense programs. Our platform gives hardware engineering teams a single place to ingest data, analyze performance, automate test execution, and collaborate across every phase of development, so they can move faster without sacrificing safety or precision. We're a fast-moving team that owns problems end-to-end, works across disciplines, and thrives at the intersection of hardware and software. We serve top-tier commercial and defense customers, from autonomy leaders like Anduril and Shield AI to next-generation aerospace teams like Hermeus and REGENT, and performance engineering teams like Pratt Miller Motorsports, alongside mission partners within the U.S. Navy and U.S. Air Force on programs where failure isn’t an option. We’re backed by Sequoia, General Catalyst, Founders Fund, Lux Capital, and Lightspeed. Our team draws from SpaceX, Palantir, Anduril, Applied Intuition, and other leading companies, united by a common mission: giving hardware engineers the tools to build the future with speed, safety, and confidence. Join Nominal as a Product Manager responsible for a product area designed to accelerate hardware engineers as they review data from test events. Your tool belt might include anything from root cause analysis frameworks, to predictive analytics and anomaly detection, to trade study analysis and dimensionality reduction and more. The users you support span multiple engineering disciplines and org maturity levels. All of this existing in the context of constantly evolving tech capability both in things like AI and traditional software. You’ll provide clarity, transforming complex technical details into a unified product that delights and empowers the users mission. You will contribute to what it means to do hardware data review in the age of AI, with a focus on what it means to create a differentiated product moat that won’t be commoditized by prompting or AI coding. This will involve diving deep into advanced analytics, capabilities that only come from scale, intelligently integrating AI agents themselves or facilitating org-wide or inter-org network effects. Your team in this role consists of software engineers and designers, along with internal stakeholders from growth. You will coordinate goal-setting, requirements gathering, vision setting, project breakdown and validation. You are skilled at soliciting and responding to feedback on both the feature goals and details alike. You use the tool that’s right for the job, whether that’s a doc, a design, or a prototype.

Requirements

Proven Product Ownership: 3–5 years of product management experience, including at least one 0→1 launch and a track record of shipping meaningful increments, ideally on an early-stage product built for technical users.
Passion for the Problem: Genuine excitement about how software is transforming the way complex hardware systems get tested and validated.
Clarity from Ambiguity: You can take a loosely defined problem space, like "how engineers root-cause an anomaly," and turn it into a concrete plan.
Deeply Collaborative: Strong cross-functional partnership with engineering and design, with a knack for aligning stakeholders, including without direct authority.
Strong Technical Intuition: You can discuss system design, data modeling, and APIs at a working level.
AI-Native Thinking: You're excited about AI agents as a product paradigm, with a clear point of view on where agents create durable advantage versus commoditized features.
Clear, Concise Communicator: You synthesize complex topics for operators, engineers, and executives alike, in writing and in conversation.
High Standards, High Ownership: A demonstrated bias toward shipping, learning, and iterating quickly, even under real constraints.

Nice To Haves

Experience in hardware engineering or adjacent technical field.
Experience working in a DoW context with a security clearance.
Experience in product design and an ability to produce prototypes to communicate ideas.
Experience in software development either in a backend, frontend or edge context.
Experience with hardware data review frameworks like FMEA, Bayesian RCA or Fishbone.
Experience with data analytics or data science especially if applied to hardware data.
Experience with data visualization time series analysis, or telemetry systems.

Responsibilities

Ideate and synthesize evidence: Work with customers and internal stakeholders to gather product ideas and evidence for investment. Apply rigor to the question of what to build, considering existing customer pain, potential markets, engineering effort, opportunity cost, and design cohesion.
Collaborate with engineering and design: Partner with engineering and design to turn ambiguous problems into clear requirements and milestones. Recommend pragmatic scope/quality tradeoffs, unblock execution, and close the loop post-launch with feedback and followups.
Be fluent in the details: You'll work closely with your engineering and design pod, and coordinate directly with the customer-facing engineers who use your product area day to day. Your job is to learn and understand the complexities so you can provide a direction that really works.
Communicate with clarity and purpose: Identify the most important thing and hone it relentlessly. Produce documents and decks, prototypes that align stakeholders and point toward proven value. You are a storyteller.
Build product systems: Nominal serves a diverse market of hardware orgs. Your responsibility is to create a product that generalizes across them, empowering the mission of one customer while contributing to systems to serve 100s more.
Ship solutions: Above all, your job is to ship product that accelerates hardware testing. You are a force for forward progress.