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

1. Own the product roadmap

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, in- vs out-of-scope definition, cost to deliver

Set priorities and dates with Engineering and Data Science; flag slippage early and make the trade-offs

Identify productization-gaps from delivery audits and analysis, and feed recurring ones back into the roadmap

2. Oversee product maturity and decide what we sell

Maintain the capability catalog: what is available now, in beta or on the roadmap, and what each can and cannot claim

Contribute to the final decision of when a capability is ready to sell (based on Data Science’s validation evidence) versus what is not-yet sellable in the pipeline, and communicate it internally

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

3. Design how results reach partners

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

Own the deliverable contents: figures, statistical summaries, methods, limitations

Embed the approved claims and the QC checklist in every template, so Pharma Partnerships can produce a correct deliverable at scale

Keep templates current as the validated envelope changes, and pull or revise one when it no longer applies

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 judge evidence: from a validation pack - back-tests, calibration, biomarker cutoffs -, you can state a claim the data supports and refuse the one it doesn't

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

You know how pharma decides: you have seen proposals, SOWs and due-diligence questions, and know what a go/no-go decision needs from a prediction

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

Therapeutic or preclinical knowledge: ADC, immuno-oncology or targeted therapy; organoid or in-vitro pharmacology

Clinical-trial design or Trial statistics: adaptive designs, sample size, endpoints

Templated reporting: report-generation frameworks or web front-end

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

Intro call (30 min) with Gustave Ronteix, CTO

Case interview (1h)

Case study (take-home)

Conversations with BD, Pharma Partnerships, the Engineering / Data Science leads and Platform Strategy & Operations.

References: 2-3, including a direct manager