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Bedrock Robotics is looking for an experienced Data Scientist to lead impactful work in autonomy and product safety. In this role, you will analyze complex data generated by autonomous systems and contribute to foundational practices within the team.
The ideal candidate will have over 5 years of experience, especially in robotics or real-time data environments, and proficiency in Python and SQL. Apply now to join a team dedicated to advancing autonomy in the construction industry.
At Bedrock, we’re moving AI out of the lab and into the real world. Our team is composed of industry veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we’re deploying autonomous systems on heavy construction machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we’re working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage.
This is where algorithms meet steel-toed boots. You’ll collaborate with construction veterans and world‑class engineers to solve physical‑world problems that simulations can’t touch. If you're ready to apply cutting‑edge technology to solve meaningful problems alongside a talented team—we'd love to have you join us.
Bedrock Robotics is hiring a Data Scientist to lead high‑impact data science work across autonomy, safety, and product. In this role, you will operate as a senior technical individual contributor, partnering closely with autonomy, machine learning, backend, and product teams to extract insights from complex, real‑world data generated by autonomous construction machines and their operators.
You will work across the full data science lifecycle (problem framing, analysis, measurement, and communication) while helping establish foundational practices for how data science is applied at Bedrock. This role is ideal for a senior‑to‑staff‑level data scientist who enjoys operating in ambiguous problem spaces, working close to production systems, and delivering insights that directly influence engineering and product decisions.