Data Scientist

Evinova delivers market-leading digital health solutions that are science-based, evidence-led, and human experience-driven. Thoughtful risks and quick decisions come together to accelerate innovation across the life sciences sector. Be part of a diverse team that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we help. Launch pioneering digital solutions that improve the patients' experience and deliver better health outcomes. Together, we have the opportunity to combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector. Conducts analysis using data science and machine learning techniques. Builds data and analysis pipelines to deliver clinical insights and reusable capabilities. Researches and implements novel methods in optimization, machine learning, generative AI, data analysis, data visualization. Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development. Collaborates in multidisciplinary cross-functional teams with world leading product managers, designers, engineers, clinicians, data scientists, biological experts, statisticians and IT professionals. in a relevant field (such as mathematics, computer science, engineering) with an outstanding track-record of industry experience (2+ years) of delivering end to end data science projects in an industry setting. Demonstrated experience and a sound understanding of a variety of statistical and machine learning methods and standard statistical/ML development practices and drive to continue to learn and develop these skills. Practical software development skills in standard data science tools: Python, Git, familiarity working in cloud environment and high-performance computing clusters. Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering). Advanced statistical and machine learning models such as hierarchical mixed Bayesian models, transformer-based NLP models, reinforcement learning, deep learning models that span CNN/RNN/LSTM, GNNs, constrained optimization, state-of-the-art timeseries & forecasting models. Experience in data-led solution delivery and software lifecycle development practices including Agile/Scrum and CI/CD within a product team.