Solution Consultant - IT & DS

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.

We are seeking a highly skilled and enthusiastic Solutions Consultant with expertise at the intersection of complex software systems and the IT and Data Science landscape within enterprise life sciences R&D. In this role, you will be instrumental in partnering directly with our customers to understand their unique IT infrastructure, data workflows, and analytical needs. You will leverage your technical expertise and understanding of Benchling to design impactful and practical solutions that streamline their operations, accelerate data‑driven discovery, and contribute to the biotech software and AI revolution.

This is an exciting opportunity to work closely not just with our customers but also our engineering, security, and product teams to shape the future of scientific software.

• Identify IT & Data Science pain points and define key success metrics: engage deeply with IT leaders, data scientists, and bioinformatics specialists at biotechnology companies to understand their critical pain points related to software systems, data management, and analysis, and collaboratively define key metrics to measure the success of Benchling in addressing those challenges.
• Engage with solutions consulting peers: work closely with R&D and business‑value solutions consultants to ensure cohesive and comprehensive solutions are presented to customers, addressing both scientific and strategic business needs.
• Design and showcase IT integrations and data pipelines: architect and demonstrate cloud‑based integrations between Benchling and other enterprise IT systems (e.g., LIMS, ELN, ERP) and develop data pipelines to facilitate data sharing, analysis, and reporting for data science teams.
• Collaborate on data‑science‑focused features: partner closely with engineers and product managers to define, prioritize, and execute on new Benchling features and integrations that specifically address the requirements of data scientists and bioinformaticians.
• Enable complex enterprise deployments with IT & Data Science focus: collaborate with professional services and customer success teams to ensure successful and scalable rollouts of Benchling at large enterprise customers, with a specific focus on integrating with their existing IT infrastructure and enabling data science (AI/ML) workflows.
• Develop targeted messaging for IT & Data Science audiences: partner with sales and marketing to develop compelling pitches and materials that highlight Benchling’s value proposition for IT departments and data science teams within the evolving biotechnology landscape.
• Contribute to IT & Data Science best practices and product development: participate in and contribute to initiatives focused on developing best practices for integrating Benchling within complex IT environments and shaping the product roadmap to better serve the needs of IT and data science users.