Ref 131214 Welcome to our sector Life Sciences. Around 3,000 colleagues worldwide make their contribution to the most important thing in life: health. From the development of vaccines and the digitalisation of the health care system to forward-looking topics such as eHealth and digital therapeutics, we place our expertise in the pharmaceutical sector, medical technology and biotechnology at the service of our renowned customers. Are you the one to explore LIFE? Your tasks and responsibilities with us - You define the use case requirements with our customers, run ideation/design thinking workshops in the areas of R&D (drug discovery, large and small molecule research, clinical study design, operations planning, etc.), manufacturing (predictive maintenance in labs, predict product quality, modelling product stability, etc.), regulatory affairs and others. - You utilise the appropriate analytics approach, design and identify the potential in the data to achieve the business objectives. - You use our accelerators (AI Studio) and frameworks (RAPIDE) to implement innovative data driven solutions using analytics & AI. - You pre-process structured and unstructured data like tables, free text, pdfs/words, images etc. - You define modelling, model selection and evaluation strategies for different business areas. - You build models using conventional machine-learning and deep learning algorithms, to obtain maximum performance for the problem in hand. - You develop automated solutions in a GxP environment. - You deploy machine learning models and apply MLOps techniques for automated retraining, inferences, and monitoring. - You communicate with cross-interface contacts (medicine, laboratory, biology etc.) to understand their requirements and to showcase your developed solution. You convince us with - A university degree in (bio-)mathematics, (bio-)chemistry, physics or in a comparable natural science field (PhD candidates are welcome). - At least 2 years of experience in a life science industry, experience in R&D product formulation, product quality or manufacturing. - Solid background in biostatistics and omics data analysis. - Advanced programming skills in R or Python and good data visualisation skills (R Shiny, Dash etc.). - Excellent analytical thinking, problem solving and collaboration skills - Experience in Data Flow pipelines (e. g. airflow) is a plus. - Familiarity with Git, Docker, basic cloud skills (AWS, GCP, Azure etc.) and experience in agile projects. - Experience in SQL and ETL is a plus. - Business fluent in English and very good presentation and communication skills, German language skills are advantageous. Kein 100%iges Match? Kein Grund zur Sorge! Capgemini Engineering unterstützt dich mit einem breitgefächerten Lernangebot, sodass du dich sowohl fachlich als auch persönlich weiterentwickeln kannst. We look forward to meeting you Do you have any questions about the job profile and/or requirements? Please get in touch with your contact person in Recruiting. Please fill in our online application form completely and attach your CV. We wish you every success for your application. Capgemini Engineering is committed to the employment of a diverse workforce. Qualified applicants are considered regardlessof their origin, skin colour, religion, gender, age, sexual orientation, gender identity, gender expression, veteran status or disability.
Data Scientist - Life Sciences (f/m/d) (Datenbankentwickler/in)