Senior Data Scientist

You will be responsible for:

• Independently manage and lead machine learning research projects and write outcomes in a scientific publication for submission to journals or machine learning conferences (ICLR, ICML, CVPR, etc).
• Collaborate with team members, propose, develop, and evaluate new machine learning models that enable understanding single-cell data and its application in drug discovery.
• Work with Ph.D. students and postdocs in collaborating teams on developing solutions for interdisciplinary scientific problems in biology, providing supervision and training to junior members of the team.
• Contribute to writing scientific papers on biotechnology and biology.
• Distill your developed solutions into open-source and easy-to-install packages with documentation that facilitates the usage of your solution for downstream users, including biologists and bioinformaticians.
• Present your research and analysis pipelines to internal and external audiences.

About You:

1. You will be supported in your personal and professional development and have the opportunity to lead peer-reviewed publications around using genetics and genomics approaches to guide drug discovery and present them at national and international conferences.
2. To be successful in the Data Scientist role, you will have the following technical skills:

Essential Skills

• To be successful in the Senior Data Scientist role, you will have the following:
• Ph.D. or MS.c with equivalent research experience in a relevant quantitative discipline (e.g., Computer Science, Computational Biology, Genetics, Bioinformatics, Physics, Engineering, or Applied Statistics/Mathematics)
• Proven experience using advanced statistical techniques, machine learning, and modern deep learning techniques.
• Previous ML work experience in scientific/academic environment (RA/Internships are considered as work experience)
• Strong knowledge of Python, including core data science libraries such as Scikit-Learn, SciPy, TensorFlow, and PyTorch.
• Knowledge of software development good practices and collaboration tools, including git-based version control, python package management, and code reviews.
• Excellent communication skills, with the ability to explain complex machine learning algorithms and statistical methods to non-technical stakeholders.
• Evidence of related work experience as a researcher in the area of Machine learning
• Strong publication record, first author position ideal

Please use the below link for job application and quicker response

https://lifelancer.com/jobs/view/e4b404ec8897586046ddf134d13c790f