Data Scientist

LabGenius Limited; Greater London; Híbrido; GBP 60.000 - 90.000; Jornada completa

Descripción de la vacante

LabGenius is seeking a Data Scientist to provide end-to-end data science support for at least one therapeutic asset, guiding the design-build-test-learn cycles of antibody optimisation. You will enable a data-first ecosystem by processing complex datasets and extracting key insights, with an emphasis on Bayesian modelling and ML techniques.

You will work in a hybrid setting with a Bermondsey office presence and occasional collaboration with wet lab scientists and software engineers to push our

Formación

• Experience solving biomedical data science problems with statistical analyses and visualisation of experimental data.
• Advanced applied statistics (Bayesian statistics, hierarchical/mixed-effects models).
• Experience deploying data analysis pipelines and code to production; proficient in Python, cloud computing, Git and SQL.
• Biological domain experience, ideally with antibody/protein sequence, structure or assay data.

Responsabilidades

• Provide end-to-end data science support for therapeutic assets from lead discovery to clinical trials.
• Drive DBTL cycles and candidate proposals for rapid experimental characterisation.
• Represent data science in cross-functional teams with wet lab, program leads and software developers.
• Onboard data pipelines, analyses, statistical models, ML models, and visualisations for experiments.
• Develop methods for antibody molecule engineering and drug development problems from target ID to pre-clinical operations.
• Tackle Bayesian and Active Learning optimisation problems; write high-quality code to maintain and enhance technology.
• Contribute to a data-first ecosystem by processing complex datasets and extracting insights.

Conocimientos

Python

Cloud computing

Git

SQL

Bayesian statistics

Hierarchical models

Data visualization

Cross-functional collaboration

Educación

MS/PhD in Biomedical Data Science or Biostatistics

Herramientas

Python (code)

SQL

Git

Cloud platforms (AWS/GCP)

Jupyter/Notebook

Descripción del empleo

At LabGenius Therapeutics ("LabGenius"), our mission is to discover the next generation of therapeutic antibodies by combining human and machine intelligence. To do this, we’ve pioneered the development of EVA™, 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.

LabGenius has raised >£55M and is backed by top-tier investors, including M Ventures, Octopus Ventures, LG Corp, Atomico, Kindred Capital, Lux Capital and Obvious Ventures amongst others.

The company is headquartered in London (UK) where we’ve established a cutting-edge antibody engineering facility. The company is staffed by a multidisciplinary team of more than 50 scientists and engineers.

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.

Our Data Science (DS) and Machine Learning (ML) team pushes the boundaries of therapeutic antibody optimisation by integrating novel DS/ML/AI tooling with our leading experimental laboratory. We oversee the design and optimisation of both monovalent VHHs and multivalent T-cell engagers, including the analyses of experimental data and subsequent ML modelling. At LabGenius, these models allow us to design molecules with previously unexplored therapeutic potential. All the work we do is focused directly on how we can progress and improve getting our therapies closer to treating patients as quickly and safely as possible.

This is a hybrid role with a minimum of 3 days per week in the Bermondsey office and up to 2 days working from home.

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 (lead optimisation, antibody engineering, assay, and automation), 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

Aside from being part of our brilliant, purpose-driven team, you’ll also enjoy:

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: Fully comprehensive healthcare through AXA, including optical and dental coverage.
• Health Cashback: Health Shield plan to claim back everyday health expenses.
• Everyday Care: 24/7 digital access to GP services.
• Fitness: Discounted gym memberships via AXA or Health Shield.
• Commute: Cycle to Work scheme for a cheaper, greener, and healthier commute.

Time-Off

• Annual Leave: 25 days paid holiday plus bank holidays.
• Life Events: 1 paid day off for moving home, plus dedicated compassionate and emergency leave.
• Sick Pay: Comprehensive paid sick leave.

Wellbeing& Culture

• Mental Health Support: Employee Assistance Programme (EAP) with direct access to coaching and CBT sessions.
• Weekly Team Lunches: Free lunches delivered weekly via Feedr.
• Socials: A regular schedule of company-wide and team-specific 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 age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race (including colour, nationality, and ethnic or national origin), religion or belief, sex, sexual orientation, or any other protected characteristic.