Senior Data Scientist - Network inference and knowledge graphs
About the Company:
Sanofi is a global life sciences company committed to improving access to healthcare and supporting the people we serve throughout the continuum of care. From prevention to treatment, Sanofi transforms scientific innovation into healthcare solutions, in human vaccines, rare diseases, multiple sclerosis, oncology, immunology, infectious diseases, diabetes and cardiovascular solutions and consumer healthcare. More than 110,000 people in over 100 countries at Sanofi are dedicated to make a difference on patients’ daily life, wherever they live and enable them to enjoy a healthier life. As a company with a global vision of drug development and a highly-regarded corporate culture, Sanofi is recognized as one of the best pharmaceutical companies in the world and is pioneering the application of Artificial Intelligence (AI) in the R&D organization including drug discovery, chemical manufacturing and control, translational research, clinical development, and regulatory document management and submission. Details of the organization and the company’s mission and goals can be found on our website (http://www.sanofi.us/l/us/en/index.jsp).
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 Digital 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 applied to single-cell RNA sequences, multi-omics data integration, and real word data (RWD); 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.
Scientists in our team come from diverse backgrounds in computational sciences and engineering with deep expertise in AI/ML, deep learning, biostatistics and algorithms.
We are seeking a Senior Data Scientist to join the AI and Deep Analytics (AIDA), Omics Data Science (ODS) team. ODS closely interacts with Precision Oncology, Precision Immunology and Translational Sciences at Sanofi R&D.
The successful candidate will have extensive experience in advanced statistics, machine learning and knowledge graph development with published studies aimed at identifying causality in complex real-world datasets. The candidate should also have excellent oral and written communication skills, the ability to learn and acquire new techniques and methodologies as well as a strong tropism for teamwork.
The candidate is expected to lead and execute analytical strategies for patient deep phenotyping using molecular, real-world and clinical data for new indication identification, disease endotype characterization and drug repurposing.
The candidate will directly report to the Global Head of AI and Deep Analytics at Sanofi R&D.
The responsibilities of the senior data scientist in AI and Deep Analytics will include:
- Applying AI/ML for modeling and embedding of data plus performing tasks such as classification, clustering, prediction, generation, relationship discovery, and causal inference.
- Building models from knowledge graphs obtained from internal and external data sources.
- Close interactions with other data scientists as well as scientists in immunology, oncology, and translational sciences, in an insertional context (US, Europe, China)
- Update and report relevant results to interdisciplinary project teams and stakeholders
- Maintain a keen awareness of recent developments in data science and bioinformatics and state-of-the-art of AI/ML/DL algorithms and research results
- Active engagement in evaluation and coordination of both academic and startup collaborations
Qualifications & Requirements:
- A PhD degree in Bioinformatics, Biostatistics, Biophysics, Computational Biology, Computer Science, and Engineering Sciences
- +5 years of industry experience with a strong record of accomplishments and project experience in applications of AI/ML in biological systems
- Experience with Bayesian analysis and causal inference
- An experience in integrating multi-omics and Real-World data would be a plus.
- Strong familiarity with core concepts in advanced statistics, machine learning, and deep learning
- Familiarity with data visualization and dimensionality reduction algorithms
- Proficiency in Python or R, SQL databases
- Ability to develop, benchmark and apply predictive algorithms to generate hypotheses
- A change agent with a combination of business, science & technology, and diplomatic skills