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iLoF

AI-powered photonics platform for drug discovery

Data Science & AI Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timePorto, PortugalNo salary listedIn-person

About the Job

Requirements

  • Several years of industry experience leading data science, machine learning or engineering teams to delivery, with people management rather than only project leadership.
  • A degree in a quantitative field such as electrical engineering, signal processing, physics, applied mathematics, statistics or computer science; an MSc or PhD is preferred.
  • A hands-on background in data science or machine learning, with a working understanding of modelling, validation and the pitfalls of small or noisy datasets.
  • Strong software engineering practice, including the ability to set and enforce standards for code quality, testing and reproducibility.
  • Hands-on experience leading the adoption of AI tools in a technical team, including choosing tools, rolling them out, setting usage guidelines and demonstrating measurable gains.
  • A track record of developing people through training design, coaching and mentoring that visibly raised team skills.
  • Proven project and delivery management experience covering planning, prioritisation, risk management and stakeholder reporting.
  • Experience running Agile delivery, such as Scrum or Kanban, including sprint planning, backlog management, stand-ups and retrospectives.
  • Hands-on proficiency in Python, SQL and Git, and practical experience building with agentic AI, including LLM agents, tool use and multi-step automated workflows.
  • Excellent communication in English with technical and non-technical colleagues.

Responsibilities

  • Manage the Data Science team day to day by setting clear expectations, running 1:1s, providing regular feedback, supporting development plans and handling performance.
  • Translate priorities set by scientific and executive leadership into sprint and project plans; allocate people, manage dependencies and track milestones.
  • Serve as the first point of contact for prioritisation questions, escalate trade-offs early and keep the team focused on key priorities.
  • Keep projects on track from scoping through validation and hand-over, flagging risks and slippage early.
  • Ensure software is built properly through version control, code review, testing, reproducible pipelines and documentation, working closely with the software team.
  • Bridge development and production-ready requirements so prototypes and models become robust, validated and deployable products.
  • Bring structure to the team's work through lightweight processes, clear definitions of done, and standards for analysis review and model validation.
  • Work across Biology, Photonics, Engineering and Clinical teams to keep data acquisition, analysis and product needs aligned.
  • Train and upskill the team by identifying skill gaps, running structured training, pairing on programming and code/analysis reviews, and bringing in external courses or experts where needed.
  • Lead AI tools strategy and implementation by setting how the team uses coding assistants, large language models, agents, AutoML and experiment tooling; selecting and rolling out tools; defining safe and rigorous usage guidelines, including data protection and validation of AI-generated work; measuring productivity and quality impact; and sharing effective practices with the wider company.
  • Report progress, risks and decisions clearly to leadership.
  • Contribute to team hiring and onboarding.

Desired Qualifications

  • Experience with signal or sensor data, including signal processing, spectroscopy, time series or instrumentation.
  • Experience in a scale-up or start-up with an AI or deep-tech component.
  • Work experience on clinically certified or other regulated products, such as CE-IVD or FDA-cleared devices or software as a medical device, or broader exposure to medtech and diagnostics.

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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