Senior Finance Manager
Helical
Senior Finance Manager
Helical
AI-driven in-silico lab for drug discovery
Helical · Luxembourg, Luxembourg · Full-time · Posted 2026-11-10
Workplace: on_site
Department: Sales & Ops
We are hiring a Senior Finance Manager to run Helical's finances and build out the finance function ahead of our Series A.
You'll be our first full-time finance hire. You'll own finance across our UK and Luxembourg entities: accounting, budgets and planning, as well as the processes and financial / operational tooling around them.
The role is tailored to someone with an accounting background and startup / scale-up experience who wants to grow with the company as the finance team expands.
We are looking for a hands-on finance professional with an accounting background and scale-up experience, who can handle the day-to-day work and build the finance function as the company grows.
You bring:
A total of 4-6 years of experience, including:
2-3 years of experience in audit, accounting or corporate finance, with a strong accounting foundation (accounting qualification such as ACA, ACCA, CPA or expert-comptable a plus);
2-3 years of experience in a start-up, scale-up or otherwise dynamic environment during a period of growth is a strong plus;
Experience with the FinOps stack (accounting software, accounts payable / expense tool, cash management tool, subscription tool etc.), ideally in the SME category;
We are expecting someone who:
Domain experience
Experience in biotech, life sciences, deep tech, or AI is a plus, but not required. Interest in what we build matters more than prior domain knowledge.
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Helical builds a virtual AI lab that turns biological foundation models into reproducible, decision-ready in-silico workflows for pharmaceutical R&D. The platform has a Virtual Lab for biologists and translational scientists and a Model Factory for ML engineers, and both share data, models, and results to bridge computational predictions with biological validation. It enables target identification, biomarker discovery, and therapeutic design by running computational workflows that generate actionable insights which are validated experimentally. The company differentiates itself by integrating biology and machine learning in a collaborative platform that creates an evidence layer linking predictions to validation, and by working with top pharma customers to shorten discovery timelines from months to days.
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