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iLoF

AI-powered photonics platform for drug discovery

Data Scientist - Applied Mathematics & Clinical Analytics

Data ScienceConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A degree in Mathematics, Applied Mathematics, Statistics, or a related quantitative discipline, supported by relevant applied experience.
  • Professional experience delivering Data Science or quantitative analysis projects from problem definition through implementation.
  • Strong scientific programming skills and the ability to write clear, maintainable analytical code.
  • Practical knowledge of statistics, machine learning, data preparation, and model evaluation.
  • Ability to investigate unfamiliar datasets, troubleshoot analytical workflows, and assess whether results are credible.
  • Experience managing personal deliverables and communicating progress, dependencies, and findings.

Responsibilities

  • Translate clinical and preclinical project questions into clear analytical tasks, approaches, and deliverables.
  • Apply mathematical expertise in signal processing, probability, and statistics to develop and evaluate robust algorithms.
  • Prepare, explore, and analyse experimental and associated clinical datasets, investigating quality issues and inconsistencies.
  • Implement and evaluate statistical and machine learning methods appropriate to the question and available data.
  • Take ownership of unresolved analytical problems, diagnose their causes, and develop practical solutions.
  • Produce reproducible code, analyses, visualisations, and documentation that colleagues can review and reuse.
  • Apply appropriate validation procedures and communicate uncertainty, limitations, and alternative interpretations.
  • Work with colleagues from other teams and disciplines to interpret findings in their experimental and clinical context.
  • Collaborate with specialist Data Scientists to apply new methods within project workflows.
  • Support reports, publications, and project milestones through clear, timely analytical contributions.

Desired Qualifications

  • Experience in a startup or another environment requiring ownership and adaptability is particularly valuable.
  • Experience analysing biomedical, clinical, or experimental data is advantageous.

About the Company

iLoF

AI-powered photonics platform for drug discovery

iLoF uses artificial intelligence and photonics to speed up personalized drug discovery by analyzing light signals from non-invasive samples to create optical fingerprints stored in a cloud library, which AI analyzes to identify biomarkers and stratify patients for trials. The platform collects light from small samples, converts it into optical fingerprints, uploads them to a cloud library, and uses AI to extract molecular and phenotypic information to guide patient screening and therapy selection under a data-subscription model. It differentiates itself by combining non-invasive photonics with a cloud-based digital library and end-to-end data services for pharma, enabling scalable biomarker discovery and patient stratification rather than offering only hardware or a single tool. Its goal is to speed up drug development by providing non-invasive, AI-driven biomarker insights and patient stratification to reduce trial costs and duration and enable more patient-centric studies.

Company size
11-50
Company stage
Early VC
Total funding
$13M
Headquarters
London, United Kingdom
Founded
2019

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