Principal Data Scientist (Bioinformatics and AI-driven Precision Medicine) - all genders
Artificial Intelligence (AI) and Machine Learning (ML) algorithms can significantly speed up drug discovery and shorten drug development and identification of patients for clinical trials thereby creating better medicines that save lives. AI and Deep Analytics (AIDA) is a critical group in Data and Data Science (DDS) organization at Sanofi R&D focused on applications of AI/ML and Deep Learning (DL) in drug design, multi-omics diseases modeling, drug development, and analysis of outcomes of clinical trials.
Our existing research and development areas include Omics Data Science; Biologics Drug Design; Natural Language Processing (NLP); Deep Learning-based Imaging and bioimaging for digital pathology and Spatial Biology; digital signal processing (DSP) and machine learning applied to digital health and patient-generated data from wearables. The 30 Scientists in our group come from diverse backgrounds in computational sciences and engineering with deep expertise in AI/ML, deep learning, biostatistics, and algorithms.
The activities of the Omics Data Science team are dedicated to the analysis of complex (multi-)omics data sets (mostly bulk-, single cell-, spatial- sequencing data and real word data). The goals of the team are to afford advanced omics data analysis to support and accelerate projects from the R&D pipeline (biomarker identification, patient stratification, indication expansion, disease endotype identification, target identification…). The team works with the state-of-the-art analytical approaches that are best adapted to solve questions from project teams but also adapts/develops tools when necessary.
We are seeking a Principal Data Scientist specializing in Bioinformatics and AI-driven Precision Medicine with a strong background in machine learning and deep learning applied to the analysis of complex omics data sets to join our Omics Data Science (ODS) team. The successful candidate will report to the Director of ODS and will work closely with all Precision Medicine groups at Sanofi R&D. The position is available in multiple locations (Germany, France, USA), but does not support immigration.
- Prepare and integrate different types of omics data (QC, batch correction…) including data from scRNAseq and spatial transcriptomics experiments
- Develop, implement, and apply state-of-the-art ML-based methods to analyze large set of (multi-)omics datasets to support and accelerate Sanofi’s R&D portfolio of projects
- Ensure that all newly developed applications are accessible to the entire community of Sanofi’s data scientists and bioinformaticians
- Work within multidisciplinary project teams in an international context (US, Europe, China). maintaining close interactions with other data scientists as well as scientists in immunology, oncology, and precision medicine departments
- Execute work plans on time, update and report relevant results to interdisciplinary project teams and stakeholders.
- Constantly monitor literature to maintain in-depth knowledge of the most recent developments in data science, bioinformatics and cutting-edge AI/ML/DL algorithms as well as the latest applications in the field of drug discovery.
- Actively engage in evaluation and coordination of both academic and startup collaborations.
Education and professional Experience
- A PhD degree in Bioinformatics, Data Science, Computational Biology, Computer Science, or Engineering Sciences
- 3+ years of industry or academic experience with a strong record of accomplishments and project experience in applications of AI/ML in biological systems
- Excellent attention to details and dedication to excellence
- Strong written, oral, and interpersonal communication skills.
- Strong aptitude to work within multidisciplinary team environment.
- Strong project management skills including organization, time management, prioritization and follow-up are key.
- Familiarity with omics data analysis (including single cell and spatial transcriptomics)
- Familiarity with Deep Learning, Neural Networks, embeddings, and Transfer Learning
- Familiarity with data visualization and dimensionality reduction algorithms
- Proficiency in Python and/or R
- Fluency in English