Data scientist

The successful candidate will have the opportunity to join a passionate and fast-growing biotech company developing novel diagnostic tests with the potential to significantly impact society Responsibilities

• Think about and conceptualize signal processing, mathematics and statistics related problems and challenges in the early cancer detection field.
• Create innovative algorithms that use signal processing to tackle genomic features as temporal-domain series.
• Study, experiment and investigate technological fields such as artificial intelligence and robotics.
• Analyze and interpret molecular, analytical and clinical data in the context of early cancer detection and identification of molecular signatures across various types and stages of cancer.
• Contribute into model, code and software improvement, and subsequently plan, scope, and execute associated research with a team of bioinformaticians, data scientists and software engineers

• MSc or equivalent experience in a relevant field such as Biomedical Engineering, Telecommunications Engineering, Statistics or Applied Mathematics with a Signal Processing specialty.
• 3+ years post-study experience applying spatio-temporal signal processing algorithms for research and/or product development, ideally in industry.
• Deep knowledge of signal processing fundamentals, application to biomedical signal (e.g., EEG, ECG) is a plus.
• Proficiency in Linux environment and bash.
• Experience in the analysis of high-throughput, quantitative technologies in genomics, epigenomics, proteomics, or transcriptomics (e.g., Hi-C, ATAC-seq, RNA-seq, MS) is a plus.
• Ability to generate tested production-ready code, version-controlled with Git.
• Excellence with computational and statistical programming, including parallelization and code optimization with Python and R.
• Ability to work with Big Data.
• Attention to detail.
• Knowledge and experience with time management and timeline development.
• Flexibility.
• Strong oral and written communication skills in English