Scientific Product Director, Clinical Prediction

About Orakl Oncology

At Orakl Oncology, we are accelerating the development of oncology treatments. Today, fewer than 5% of new cancer drugs succeed in clinical trials. Clearly, new methods are needed. We combine cutting-edge biology and AI to build the next generation of insight platforms with the world's largest cohort of patient tumor avatars. These avatars fuel our AI-powered predictive engine, helping to anticipate clinical trial outcomes, validate therapies, and uncover new drug candidates. By generating multimodal, real-world data, we deliver insights that consistently outperform existing solutions.

Our mission is simple yet ambitious: to bring more effective treatments to patients who need them - and to make drug development smarter, faster, and more personalized. We collaborate with top hospitals, research institutes, and pharmaceutical companies worldwide. Backed by leading investors, we are a fast-growing, mission-driven startup at the intersection of science and technology.

The role

Our clinical-prediction offer gives pharma partners the evidence to guide decisions before and during clinical development. We are looking for a Scientific Product Director to turn this science into sellable products: decide what gets developed and when, define what each capability can claim and output, and shape how results are delivered to partners.

You will report to Gustave Ronteix, CTO and co-founder, and work daily with a tight-knit interdisciplinary team composed of Computational Biology, Data Science, R&D, Platform Strategy & Operations, BD and Pharma Partnerships.

What you'll do

• Design and build a scalable product capable of derisking and accelerating clinical development of drug candidates based on Orakl’s scientific capabilities

• Turn signals from BD, Pharma Partnerships and R&D into capability definitions: specs, target metrics, validation plan, cost to deliver, etc.

• Set priorities and timelines with the internal teams

• Identify productization-gaps, quality issues and feed back the ajustements into the product roadmap

• Maintain the capability catalog: help guide scientists and researchers to what we can do

• Own the product delivery gates: for each novel capability and product improvement, design the QC and validation steps

• Oversee the scientific case for each capability: white papers, application notes, posters

• Design the reports, data packages and dashboards partners receive, and direct the engineers who build them

What we're looking for

Must have

• PhD or equivalent in cancer biology, pharmacology, biostatistics or computational biology

• 8+ years in translational oncology, biomarker or diagnostics development, computational-biology platforms or preclinical CRO services, including 2+ owning a product roadmap

• Technical depth: you read and understand production code, and can brief and review the work of engineers who build our reports and dashboards

• You can judge evidence: from a validation pack, and this is backed by strong quantitative skills

• You have experience working at the intersection of scientific and business departments within fast-growing companies

• You know how pharma operates: you have contributed to proposals, SOWs and due-diligence questions, and know what a go/no-go decision by pharma requires

• Fluent in English

Nice to have

• You have seen bespoke research work turned into something repeatable and sellable

• Scientific authorship: Posters, talks, papers or white papers; a presence at AACR, ASCO, ESMO or SITC

• Regulatory: exposure to regulated or quality-managed environments

What we offer

• Mission: work on the forefront of cancer research

• Ownership: a product function to build from the ground up

• Impact: pharma teams make real portfolio decisions with what you define

• Team: an exceptional crew of clinicians, biologists, engineers and data scientists, most with a PhD

👉 More about Orakl here and here

Interview process

1. Intro call (30 min) with Gustave Ronteix, CTO

2. Technical interview (1h)

3. On site case study followed by conversations with BD, Pharma Partnerships, the Engineering / Data Science leads and Platform Strategy & Operations

4. References: 2-3, including a direct manager