For one of our clients, a pharma company located in the Walloon Brabant, we are looking for an experienced Data Scientist with a background in (bio)chemical engineering, to come on board and join their Drug Substance Innovation Centre. This position is an hybrid role (min. 2 days/week on site at client's location).
Job Description
The Data Scientist integrates and analyses complex, high dimensional data sets to extract biological knowledge relevant for R&D. This role ensures advanced data analytics and bioinformatics deliverables for R&D projects are at the top of research and industry standards with respect to scientific excellence, quality and timelines.
Responsibilities
- Bioinformatics/data analytics activities for R&D;
- Data and knowledge integration for hypothesis generation;
- Data modelling for innovative assays, high-dimensional readouts and microbial genomics;
- Development of tailored systems and analytical models for exploitative analytics of pre-clinical, clinical, and epidemiological data;
- Development of analysis pipelines using combinations of heterogeneous, high dimensional datasets and tools;
- Advise on study design, readout selection and data formats, data analysis strategies;
- Preparation and publication of scientific papers and congress reports.
Requirements
- MS in Data and Computer Sciences, Complex Systems, Mathematics and Physics, Biological and Systems Engineering, Bioinformatics, Computational Life Sciences or equivalent with a first experience in the biopharma industry or a PhD in the field of Data Science/(bio)chemical engineering.
- Fluent in English
- Experience in using Python and Pandas.
- Good understanding of mass balances and metabolic fluxes.
- Experience in working with large set of data.
- Demonstrated proficiency / publication record in one or more of the following areas: computational and molecular epidemiology; bio-informatics and genomics; systems vaccinology and immuno-informatics; data mining and machine learning; computational/dynamic modelling; high performance scientific computing infrastructures
- Good programming, data analytics and modelling skills
- Good business understanding of the Pharmaceutical industry
- Good knowledge of vendors and state-of-the-art solutions for Data Science and Digital Innovation
