Senior Data Scientist | Personalized Medicine | Deep Tech Startup

Ilof Intelligent Lab On Fiber; Porto; On-site; EUR 45,000 - 75,000; Full time

Job summary

IloF Intelligent Lab On Fiber in Porto seeks a Senior Data Scientist for a hybrid role focusing on developing data science methods for biomedical and optical data. The ideal candidate will have a PhD or Master's degree in a related field and at least 3 years of post-PhD experience. Responsibilities include working on complex data problems, analyzing biomedical datasets, and collaborating with cross-functional teams. This position offers a unique opportunity to contribute to high-impact projects in a fast-paced startup environment.

Qualifications

• Experience with biomedical spectroscopy data or other high-dimension data.
• 3+ years of post-PhD experience in academia or industry.
• Ability to work in interdisciplinary teams.

Responsibilities

• Own the full data science workflow for specific projects.
• Analyse proprietary biomedical datasets to identify patterns.
• Develop statistical and machine learning methods for noisy data.

Skills

Applied statistics

Predictive modelling

Experimental design

Data preprocessing

Feature engineering

Exploratory analysis

Communication skills

Education

PhD in related field

Master's degree with strong research experience

Tools

Machine learning methods

Chemometric analysis

Job description

Senior Data Scientist | Personalized Medicine | Deep Tech Startup

Full-time

At iLoF, you will develop data science methods that extract reliable signals from biomedical and optical data. The role sits at the intersection of modelling, signal processing, and experimental science, with a focus on noisy, high‑dimension, and biologically complex datasets.

This is a hybrid role with onsite training and a minimum of 5 days per month on‑site. Greater on‑site availability is a plus.

• Own the full data science workflow for specific projects, from problem framing to delivery.
• Analyse proprietary biomedical datasets to identify patterns, variability, and opportunities for improved performance.
• Develop statistical and machine learning methods for noisy, high‑dimension, and often small‑sample data.
• Design and evaluate robust validation strategies, including uncertainty and robustness checks.
• Improve preprocessing pipelines, signal quality, and acquisition protocols through work with raw data and instrumentation.
• Apply chemometric and multivariate analysis to spectroscopic data.
• Work cross‑functionally with experimental, hardware, and product teams.
• Communicate findings, trade‑offs, and recommendations clearly to technical and non‑technical stakeholders.
• Contribute to reusable analysis frameworks and internal best practices.
• Stay up to date with the latest advancements in data science, computational modelling, and advances in spectroscopy for clinical applications.
• Contribute to research publications, patents, and presentations at leading conferences.

Who we are looking for?

• You are a hands‑on Data Scientist who is comfortable working in a fast‑paced startup environment and tackling complex scientific problems with real analytical consequences.
• You have experience with biomedical spectroscopy data or with other high‑dimension data where noise, batch effects, measurement artefacts, and instrument‑driven variation must be handled carefully.
• You are strong in experimental design, validation strategy, and communicating uncertainty, trade‑offs, and limitations clearly.
• You work well in interdisciplinary teams and enjoy collaborating with scientists and engineers across biology, hardware, and product.
• PhD in Computer Science, Applied Math, Statistics, Physics, Engineering, or a related field. Exceptional candidates with a Master’s degree and strong research experience will also be considered.
• 3+ years of post‑PhD experience in academia or industry working on quantitative data problems.
• Strong experience in applied statistics, predictive modelling, and experimental design.
• Experience working with raw data alongside instrumentation, including optimisation of signal quality, acquisition protocols, or hardware performance.
• Plus: Experience in chemometric or multivariate analysis of spectroscopic data such as Raman, FTIR, or related high‑dimension signal data.
• Strong data preprocessing, feature engineering, and exploratory analysis skills.
• Experience designing robust validation strategies and interpreting model performance in ambiguous or noisy settings.
• Strong problem‑solving ability and comfort with incomplete, messy, or evolving data.
• Excellent written and verbal communication skills.
• Experience mentoring junior team members is a plus.

This is a unique opportunity to work on high‑impact projects at the intersection of theory and experiment, developing models that shape cutting‑edge technology and scientific discoveries.