Associate Data Scientist | Personalized Medicine | Deep Tech Startup at iLoF

Porto, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

07 Jul, 26

Salary

0.0

Posted On

08 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data science, Statistical modelling, Machine learning, Signal processing, Chemometrics, Multivariate analysis, Spectroscopy, Raman, FTIR, Experimental design, Data preprocessing, Feature engineering, Predictive modelling, Biomedical data analysis, Python, Communication

Industry

Biotechnology Research

Description

Company Description At iLoF, you will help 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-dimensional, and biologically complex datasets. You will work with raw data generated on in-house instruments, helping improve signal quality, acquisition protocols, and hardware performance. You will also apply chemometric and multivariate methods to spectroscopic data such as Raman and FTIR, turning complex measurement signals into more reliable and interpretable insights. You will work closely with experimentalists, hardware specialists, and product teams, directly influencing experimental design, data interpretation, and technology development — creating a tight feedback loop between theory and practice. This is a high-impact role in a growing team. We are looking for someone who combines strong technical foundations, scientific curiosity, and the ability to learn and execute well in a fast-moving environment. * This is a fully onsite position, based at our Porto office Job Description You will: Support the data science workflow for specific projects, from problem framing to delivery. Analyse proprietary biomedical datasets to identify patterns, variability, and opportunities for improved performance. Help develop and apply statistical and machine learning methods for noisy, high-dimensional, and often small-sample data. Contribute to validation strategies, including uncertainty and robustness checks. Help 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, documentation, and internal best practices. Stay up to date with developments in data science, computational modelling, and spectroscopy for clinical applications. Contribute to research publications, patents, and conference presentations where relevant. Who we are looking for You are a hands-on Data Scientist who is comfortable working in a fast-paced startup environment and wants to grow by tackling interesting scientific problems. You are happy moving between exploratory analysis, statistical modelling, signal processing, and practical delivery, with support and guidance from more experienced colleagues. You may have experience with biomedical, spectroscopy data, or other high-dimensional data where noise, batch effects, measurement artefacts, and instrument-driven variation must be handled carefully. You are developing your skills 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. You care about scientific rigour, learning quickly, and turning complex data into models and insights that can make a real difference. Qualifications Master’s degree or PhD in Computer Science, Applied Math, Statistics, Physics, Engineering, or a related field. Exceptional candidates with relevant research or applied experience will also be considered. Around 1–3 years of experience in academia or industry working on quantitative data problems. Strong foundation 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-dimensional signal data. Strong data preprocessing, feature engineering, and exploratory analysis skills. Experience supporting 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. Interest in mentoring and learning from senior colleagues is a plus. Additional Information iLoF in a nutshell 💡 As personalized medicine becomes the norm, scientists, patients, and healthcare systems worldwide face massive barriers in providing the right treatment to the right patient. Recognized by CB Insights and Financial Times as one of the most promising Digital Health companies in the world, iLoF is building an AI-powered platform capable of transforming precision medicine. Our goal is to become the platform that democratizes access to personalized medicine for millions of people living with complex diseases around the globe. Thanks to our proprietary optical fingerprint library of disease biomarkers and biological profiles we can offer personalized patient screening and stratification in a faster and more affordable way, saving up to 40% of the cost and 70% of the time while enabling a more human patient experience. Supported by leading institutions like Microsoft Ventures, Mayfield, and the Oxford University, iLoF is currently focusing on validating its platform technology in one of the biggest challenges of our times: Alzheimer's, while maintaining ongoing verticals on Digestive Cancer, Stroke, and Infectious diseases. Our Team 🧑🏻‍💻 We are a mix of scientists, entrepreneurs, and inventors based in Oxford and Porto, with a passion for healthcare! Recognized by CB Insights as one of the most promising Digital Health companies in the world and by the Financial Times as a Transformational Business in Healthcare, iLoF has been regularly featured in leading outlets like Tech Crunch, Wired, and Sifted and listed as a rising star in AI-Driven Drug Discovery, Health Screening & Data Analytics. What we value A Be Kind attitude is the main guideline within iLoF A hand in the hammer and another free to support your co-workers as a true team player An honest and egoless attitude towards discussions and critics working in good faith The braveness to speak your heart in any situation Through words or actions be always sure to make a difference at any moment! Be proud to drive your responsibilities to success and help others do the same, embracing ownership! Perks 😉 An exciting future with a deep-tech company selected by Financial Times and CB Insights as one of the most transformative companies in the world A high‑paced, flexible environment: adaptable working hours, strong remote work culture A stimulating atmosphere with room for creativity – fast‑paced, fun, and energetic start‑up with a friendly culture Weekly happy hours with amazing food and drinks Free coffee and snacks ☕ The opportunity to work with a world‑class, talented team – and potentially change healthcare as we know it for millions of patients living with complex diseases around the globe 🧑‍⚕️ We share a passion for being part of a mission that matters, and we are always looking for curious and collaborative people who share our values and want to be part of our journey. If that sounds like a fit for you, click the apply button and join us. You’ve read all this way but you’re missing a skill or two? No problem, it’s our job to upskill you to take your career to the next level. What we’re trying to say is, don’t be afraid to apply if you don’t tick all the boxes.

Responsibilities

You will develop data science methods to extract reliable signals from complex biomedical and optical datasets while working closely with experimental and hardware teams. The role involves improving signal quality, applying statistical and machine learning models, and contributing to validation strategies for clinical applications.