Senior Bioinformatic scientist

You will join a multi-disciplinary team of software engineers, bioinformaticians, and biologists to tackle the most burning questions of the pharmaceutical industry using cutting-edge data. You will focus on deciphering disease mechanisms, identifying biomarkers of drug response, identifying novel drug targets, and predicting combinations. All are based on human clinical and molecular data empowered by the company disease model. This role is customer-facing. You will be working with the best pharma companies in the world to bring novel therapies to patients.

Responsibilities:

• Leading efforts to optimize and improve existing single-cell and omics and deconvolution pipelines to improve quality, efficiency, and scalability.
• Taking responsibility for developing, integrating, and supporting complex components within the company.
• Providing expert guidance and training to bioinformatics scientists, fostering a culture of continuous learning and development within the team.
  
  

• Master’s degree in Bioinformatics, Computational Biology, or a related field, with 5+ years of proven experience working on single-cell data, or - PhD with 2+ years of proven experience working on single-cell data.
• Advanced Programming Skills: Strong proficiency in Python and R.
• Expertise in analyzing large-scale single-cell datasets and data integration.
• Experience with multi-omics data integration and analysis.
• Experience in developing, optimizing, and maintaining scalable and reproducible pipelines.
• Experience in leading bioinformatics projects from conception to completion, including managing timelines, resources, and collaboration with cross-functional teams.
• Experience with package development and documentation
• Strong communication skills with fluency in English.
• Team player, positive and driven.
• Attention to detail and fast learner.
• Ability to mentor and lead
  
  

• Experience with database management systems, and familiarity with cloud computing environments (e.g., AWS, Google Cloud) for handling large-scale bioinformatics datasets.
• Expertise in applying deep learning techniques to bioinformatics problems, particularly in single-cell data analysis.
• Familiarity with neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and other advanced models used in the analysis and interpretation of high-dimensional single-cell data
• Public speaking
• Leadership experience – managing a team or a squad