Data Scientist / Computational Biologist - all genders

Sanofi S.A.
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Job Description

In our fight against autoimmune diseases, we seek a computational biologist/data scientist to lead the RNASeq and multi-omics analysis efforts. In this exciting role as a part the interdisciplinary Immunology and Inflammation Therapeutic Area in Frankfurt you will perform data analysis of big datasets for drug discovery programs and the identification of novel targets. In this hands-on role you will need to design high content experiments, to manage data, and to use advanced analytical and computational techniques to advance our portfolio and biomarker strategy. The TA Immunology group in Frankfurt has extensive experience in immunology and autoimmunity and offers an excellent working environment and interacts very closely with the digital ecosystem of the German Hub. You will be part of a group of passionate scientists, mentored by different experts and closely collaborating within and across departments.

Main responsibilities

  • Analyze complex biological datasets from a range of technologies and sample types
  • Analyze and utilize best practice for bulk RNASeq and single cell methods including data normalization, statistical modeling, deconvolution, cell type/state analysis, cell to cell interaction
  • Development and implementation of novel bioinformatics methods and visualization of complex data sets for internal use
  • Generation of analytical approaches on multi-omic based molecular profiling of patient cohorts to comprehensively understand the MoA on different levels of biology, disease subtypes and patient stratification for target and biomarker identification
  • Proactively engage with project teams to define clear scientific questions that can be addressed with appropriately powered experimental designs
  • Apply scientific expertise and judgement to initiate, design, direct and execute experiments and/or studies in support of research projects. Analyze, interpret and present results
  • Provide expertise and technical consultation for external collaborations/partnerships in academia and industry

About you:

  • Passionate, self-driven team player with analytical skills and interest to work in a highly interdisciplinary team
  • Ph.D. in computational biology/bioinformatics or immunology with strong experience in data science
  • Prior expertise in analyzing and integrating bulk RNAseq, scRNA-seq, CITE-seq, flow cytometry and metabolomics datasets as well as multi-omics data integration and biological network inference
  • Expertise in immunology including automated flow cytometry analysis and single cell experience
  • Comprehensive experience with clinical data sources for gene expression, mutations, and related platforms (TCGA/GTEX/Human Cell Atlas)
  • Experience with Arraystudio, IPA, Spotfire
  • Expertise in the analysis of complex data sets and their interpretation, e.g. using R or Python on a high-performance cluster such as Git, Docker or cloud environment
  • Experience with machine learning/deep learning techniques is a plus
  • Analysis of epigenetic or spatial transcriptomics data is a plus
  • Excellent oral and written English language communication skills, knowledge of German is a plus

Pursue Progress. Discover Extraordinary.

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

Company Info.

Sanofi S.A.

Sanofi is comprised of three core business units: Specialty Care, Vaccines and General Medicines. Consumer Healthcare will become a standalone business unit. Around the world, more than 100,000 people at Sanofi are dedicated to making a difference in patients' daily lives, wherever they live, and enabling them to enjoy a healthier life.

  • Industry
    Healthcare
  • No. of Employees
    12,500
  • Location
    55 Corporate Drive, Bridgewater, NJ 08807, USA
  • Website
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