Data Scientist - Digital Biomarkers
Posted on Aug 27, 2020 by Harvey Nash IT Recruitment Switzerland
For our client in Basel we are searching for Data Scientist - Digital Biomarkers for 6 months project
Job Title: Data Scientist - Digital Biomarkers
Duration: 15/09/2020 to 14/03/2021
Our ability to accurately quantify changes in disease state determines how well we can demonstrate that our drugs improve the quality of life of our patients. Traditional disease assessments commonly suffer from reliability issues, ceiling effects and a lack of standardisation. We believe Digital Health sensors and advanced analysis techniques will provide us with a better and more objective insight into disease through instrumented clinical tests, unsupervised digital assessments at home and passive monitoring. Our Digital Endpoints team in Global Drug Development are bringing these technologies into clinical trials.
We are seeking a data scientist, with experience in Digital Biomarkers, such as expertise analysing data from mobile medical devices, Digital Health sensors, large multivariate clinical data sets and real-world data (such as medical claims). We believe the clinically meaningful information derived from such technologies (Digital Biomarkers) will help us unleash the power of data and digital in our clinical trials and beyond.
The successful candidate will have diverse applied experience across the domain of Digital Health (wearables, ambient monitors, physiological, etc.) including the assessment of novel technologies, deployment into clinical studies, and be familiar with medical device processes such as technical and clinical validation. Specifically, tasks may include analysing Digital Health sensor data, evaluating and implementing published algorithms on clinical datasets, establishing software frameworks for efficient and effective data exploration, and performing statistical analyses on Digital Biomarker data.
. MSc. (with 3+ years of experience) or PhD in in a quantitative discipline (eg Applied Mathematics, Computer Science, Bioinformatics, Epidemiology and Statistics; can also consider Operations Research, Industrial Engineering, Decision Science, Quantitative Research, Econometrics, Computational Physics/Chemistry/Biology)
. Experience in working with complex numerical challenges/tasks
. Experience with applied (bio)statistics required (eg, mixed effects models)
. Experience with longitudinal data analysis is a plus
. Experience in medical field or analysis of human behavior is a plus
. Fluency in Python required
. Fluency in R, and/or Matlab is a plus
Experience in digital biomarker validation is a plus