Data Scientist in London

At LabGenius Therapeutics, our mission is to discover the next generation of therapeutic antibodies by combining human and machine intelligence. We’ve pioneered the development of EVA™, a state-of-the-art automated platform, enabling the closed-loop discovery of high-performing, non-intuitive antibody designs using proprietary, ML-grade datasets. For our wholly-owned therapeutic pipeline, we’re using our closed-loop discovery engine to establish a pipeline of highly selective T-cell engagers and ADCs for the treatment of solid tumours.

As a Data Scientist at LabGenius, you will provide end-to-end data science support for at least one therapeutic asset as we aim to progress from lead discovery all the way to clinical trials. You will drive the “design” and “learn” cycles of the “design-build-test-learn” that forms the basis of our therapeutic antibody optimisation cycles at LabGenius, including the proposal of candidates for rapid experimental characterisation. You will enable a data-first ecosystem at LabGenius through your proficiency at processing complex datasets and extracting key insights.

What you’ll do in this role:

• Provide end-to-end data science support for at least one therapeutic asset as we aim to progress from lead discovery all the way to clinical trials.
• Drive the “design” and “learn” cycles of the “design-build-test-learn” (DBTL) that forms the basis of our therapeutic antibody optimisation cycles at LabGenius, including the proposal of candidates for rapid experimental characterisation.
• Represent data science in highly cross-functional teams, including wet lab scientists, scientific program leads, and software developers.
• Onboard rigorous data pipelines, analyses, statistical models, machine learning models, and visualisations for experiments that allow us to better understand the therapeutic potential of our antibodies.
• Implement and develop novel methods for a variety of applied antibody molecule engineering and drug development problems, from target ID to supporting pre-clinical operations.
• Work on challenging statistical problems using Bayesian modelling; and optimisation problems using Active Learning & Bayesian Optimisation.
• Write high quality code to maintain and enhance our technology.
• Enable a data-first ecosystem at LabGenius through your proficiency at processing complex datasets and extracting key insights.

What we’re looking for:

• Experience working on challenging biomedical data science problems, including the statistical analyses and visualisation of experimental data.
• Advanced applied statistics e.g. Bayesian statistics, hierarchical / mixed-effects models, etc.
• Experience with putting data analysis pipelines and code into production, including proficiency with python, cloud computing, git, and SQL.
• Biological domain experience, ideally including experience working with the sequence, structural or assay data for antibodies or other proteins.
• Ability to work collaboratively in highly cross-functional teams, especially with wet lab scientists and software engineers.
• Advanced education (MS or PhD) in a relevant domain (e.g. biomedical data science, biostatistics).

What you’ll receive from us:

• Financial Bonus: Discretionary, performance-linked bonus scheme.
• Equity: Generous stock option plan.
• Pension: 5% company contribution, plus an extra top-up on our tax savings.
• Financial Security: 3x salary Life Assurance and Income Protection.
• Health & Wellness: Private Medical Insurance, Health Cashback, Everyday Care, Fitness discounts, and Cycle to Work scheme.
• Time-Off: 25 days paid holiday plus bank holidays, 1 paid day off for moving home, and comprehensive paid sick leave.
• Wellbeing & Culture: Mental Health Support, Weekly Team Lunches, and regular social events.

Diversity & Inclusion: We believe that diverse perspectives build innovative, exceptional teams. As an equal opportunity employer, we do not discriminate on the basis of any protected characteristic. If you don't feel like you meet every single requirement of this role, we still want to hear from you!