Senior Principal Computational Biology Scientist

Position Overview:
The Translational Sciences Group in Sanofi strives to generate scientific knowledge that translates into transformative therapies for patients with unmet medical needs. Translational Sciences is building a world-class translational research team that is passionate to contribute to the discovery and development of novel therapeutics for patients. The translational research scientist will work closely with the Head of Translational sciences, USA and group heads, laboratory heads and internal and external partners to ensure the progression of the translational sciences research portfolio and support operational excellence across the group. As a member of the leadership team, the translational research scientist will ensure key portfolio and project reviews, facilitate alignment among key internal and external stakeholders, identify major gaps and roadblocks and work closely with the head of translational sciences to take actions to overcome them. This role will report to the Head of Translational Sciences, US and is expected to have a strong impact on the deliverables of Translational Sciences.
The successful candidate will be an expert in the application of multi-omics in drug discovery and development, and has experience operating in a matrixed drug discovery environment. In this position, the successful candidate will be working closely with scientists who play a major role in the evaluation and employment of the emerging cutting-edge Multi-omics technologies as well as for maintaining operational readiness of the equipment. This exciting role will afford talented scientist the opportunity to help translate the translational research into major portfolio contributions by creating clear alignments by working closely with the Head of Translational Sciences, US.
Summary of Key Responsibilities:
- Perform integrative analyses of multi-omics data to support drug discovery and development activities such as biomarker identification by designing and developing analytical pipelines along with data integration methodologies to enable mining of large complex datasets.
- Collaborate with scientists to develop data infrastructure with analytical pipelines, implement novel algorithms to manage and build analytical solutions to accelerate the analyses of transcriptomics, genetics, proteomics, metabolomics and multi-omics data from various studies.
- Develop and/or implement informatics solutions with proper data governance and management guidelines to create harmonized datasets to enable rapid automation of analytical capabilities.
- Integrate and lead hypotheses generation from multi-platform and diverse datasets by employing sound computational biology approaches, for various aspects of drug discovery and development, in a pan-therapeutic manner.
- Develop and apply innovative and creative computational approaches to understand complex disease conditions using multi-dimensional -omics and clinical data.
- Contribute to projects to demonstrate impactful delivery of analyses to Identify candidate therapeutic targets and biomarkers for indications of interest, through integrated analysis of high-throughput molecular data, real-world data and clinical phenotypes.
- Evaluate and develop new technologies to streamline and improve the efficiency of the workflows. Effectively manage data, tools and methodologies to improve analytical ability of proteomics and metabolomics data, which may include data ingestion, integration, multi-omics analytical analyses, visualization and interpretation to develop actionable hypotheses.
- Prepare publications, research and clinical/regulatory documentation in accordance with Sanofi quality standards. Author technical reports, study protocols and manuscripts for publication; present at internal and external meetings and conferences.
Basic Qualifications:
- PhD in Computer Science, Computational Biology, Bioinformatics, Data Science, Proteomics or a related discipline with at least 10 - 12 years of industry experience.
- Proficiency in genomics, genetics, spatial transcriptomics, proteomics and metabolomics analyses, relevant analytical tools and software packages.
- Demonstrated leadership experience in managing small groups of PhD level scientists and matrixed projects at various stages of drug discovery and development.
- Demonstrated experience in Rmarkdown or Jupyter employment in a computing environment. Working in Linux, high performance computing environment and cloud environment (AWS) with various data management platforms and data visualization approaches.
- Proven track record of publishing relevant bioinformatics, computational biology and multi-omics peer-reviewed journals.
- Highly motivated, organized, detail-oriented and able to work in a fast-paced environment and must be able to work in a team-oriented environment.
- Strong written and verbal communication skills are essential. Desire to function independently and successfully in a cross-functional, matrix-based research organization.
- Must be able to work in a team-oriented environment and demonstrate attention to detail and record-keeping.
- Strong communication and inter-personal skills.
Preferred Qualifications:
- Demonstrated experience, knowledge and application of statistical approaches and data modeling to large scale life-sciences data.
- Ability to develop, benchmark and apply predictive algorithms on multi-omics datasets to identify novel biomarkers, dissect gene/disease relationships and generate hypotheses.
- Proficiency in analyzing data with R/Bioconductor, Python, Matlab or Pipeline pilot. Working knowledge of Linux/HPC and shell scripting.
- Strong interested in biology and caring for developing novel therapeutic intervention strategies for patients with unmet disease conditions, and an ability to liaise with scientists from multiple therapy areas to help define and address biological questions with computational and analytical approach.
- Proficiency in biostatistics, linear/non-linear regression models, dimensionality reduction, clustering, and knowledge of artificial intelligence and machine learning approaches (e.g. classification, clustering, artificial neural networks, deep learning) on multi-omics data sets (biomarker profiles, genome-wide datasets, medical imaging data, continuous data) is a plus.
- Excellent written and oral communication skills.
- Excellent interpersonal and team skills.
- Established publication record.
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
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