About the role
We are rebuilding biotech for the AI era. When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done. Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma. We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves. AI fluency is the foundation we build on; it's core to
how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today. ROLE OVERVIEW This is a 6 month contract in-office role with a required hybrid schedule — a minimum of three days per week (Monday, Tuesday, and Thursday) at our San Francisco HQ. Our marketing data layer was built incrementally over several years, and it shows. The models, dashboards, and pipelines powering our funnel reporting, campaign attribution, and SDR workflows have accumulated patches and gaps that are increasingly holding us back particularly as we push into AI-driven marketing tooling that requires clean, well-documented data to work reliably. We're looking for a mid-level marketing data analyst for a focused 6-month engagement embedded with the Marketing Operations team. You'll own the sprint to clean up the underlying data models, ship the core dashboards we've been scoping, integrate new data sources, and document everything well enough that
