Helical
Senior Scientist (Comp. Bio/ML)

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About the Role
We’re looking for a Senior Computational Scientist to help translate our foundation models into impactful, real-world discovery workflows. In this role, you’ll provide scientific leadership across model evaluation and applied use cases, ensuring our work stays grounded in the most relevant challenges in drug development and translational research.
Responsibilities
- Join as a senior individual contributor, reporting to the Head of Computational Biology, with the opportunity to grow into management as the team scales.
- Act as a key scientific partner to our research team.
- Mentor and support junior colleagues.
- Work closely with Product and Business Development to turn cutting-edge biology + ML into deliverables that matter for customers.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements


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- PhD in Computational Biology, Machine Learning, Bioinformatics, or a related field, with a strong focus on early drug discovery + ML, and 2+ years of industry (non-academic) experience OR MSc in a relevant field and 5+ years of industry experience applying ML to early drug discovery problems
- Strong understanding of ML/AI methods for biological data (e.g., transformers, VAEs, diffusion models, classical ML)
- Hands-on experience with modern ML frameworks such as PyTorch (or equivalent)
- Leadership experience with small teams to work towards defined roadmaps or projects
- Excellent communication skills — able to translate complex science into clear, actionable insights for technical and non-technical stakeholders
- Comfortable in a fast-paced, high-iteration environment, moving quickly from prototype → experiment → insight
- Strong passion for building at the intersection of biology and machine learning
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