Head of Business Development

ABOUT the company

The company is a clinical AI research lab working at the intersection of multi-modal AI and precision medicine. Our goal is to make disease predictable. To accomplish this, we develop new AI methods that predict patient outcomes and treatment response, and build clinical tools to assist physicians in selecting the most optimal treatments for their patients.

Our AI research lab discovers and develops methods to recognize patterns and predict outcomes across complex, multi-modal clinical data. This spans our causality [link for members] (the company™ Tau), foundation model [link for members] (Falcon and Kestrel for digital pathology), and survival analysis [link for members] research.

Our first clinical products, such as the company™ Breast [link for members] for breast cancer, already help patients get the most appropriate treatment across the best academic institutions and community clinics worldwide.

At the company, you will have a unique opportunity to shape not only the future of our company, but also the future of healthcare. You will join an exceptional team at the forefront of clinical AI research and deployment. Our advisors include AI pioneers such as our founding advisor, Yann LeCun, and distinguished oncologists from top cancer research institutions, all united by the mission to redefine precision medicine.

The company has raised over $24 million in funding, including a $20 million Series A led by top venture capital funds such as Thiel Capital/Founders Fund (OpenAI, SpaceX, Palantir), Obvious Ventures (AMI Labs, Inceptive, Radical Numerics, Recursion), and AIX Ventures (Hugging Face, Perplexity).

We are an company with a flat organizational structure, where every team member is empowered to actively contribute. Leadership roles are earned by those who demonstrate initiative and consistently deliver exceptional results. Strong work ethic and the ability to prioritize ruthlessly are essential.

RESPONSIBILITIES

You will build the company's pharma partnership business from the ground up. The company has developed prognostic and predictive AI models validated in breast cancer, with potential applications across drug development, such as companion diagnostics, biomarker discovery, patient stratification, and trial rescue. This role owns pharma as a revenue stream alongside our diagnostics business. In that process, you will:

• Identify target companies, map the decision unit inside each, run outreach, and lead negotiations to signature.

• Construct novel applications of our technology against each company's development pipeline and translate them for scientific, clinical, and business audiences.

• Build and maintain relationships with the people inside pharma who sponsor and fund partnerships.

• Bring pharma priorities and unmet needs back to our research and product teams.

• Work with research, clinical, product, and legal to scope what we commit to, structure the terms, and get agreements signed.

• Work directly with the CEO on pipeline, forecast, and deal strategy.

QUALIFICATIONS

• 8+ years in pharma and/or diagnostics business development, from inside pharma or from a diagnostics or technology company selling into pharma.

• Preferred: MD, PhD, PharmD, NP, or a Master’s degree in cancer biology, molecular biology, cell biology, biomedical sciences, pharmacology, pharmaceutical sciences, or a related life sciences field.

• Documented track record of leading or co-leading pharma deals in companion diagnostics, biomarkers, patient stratification, or similar. If you did not formally lead one, we want evidence you were pivotal in getting it done.

• Built a pharma partnership pipeline from scratch, or decided from the pharma side which partnerships got funded.

• Fluency in how pharma makes partnership decisions: who decides, where the budget sits within a business unit, and how deals actually get pushed through.

• Relationships across large and mid-cap oncology pharma that you can activate now.

• Comfortable doing deep on technical material, with a history of finding non-obvious applications for it.

• Bias for action.