Translational Bioinformatics Scientist at Tempus
Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
We are seeking an independent and motivated Translational Bioinformatics Scientist to join our Research group.
What You'll Do:
You will work on an interdisciplinary team to develop new computational and statistical approaches to support precision medicine applications. The successful candidate will work in an interdisciplinary team, carry out data analysis, apply and develop best-in class algorithms that directly address important biological and clinical questions, and provide strategy and input on new products and services.
- Advanced degree (Masters or PhD) in bioinformatics, statistics, biostatistics, epidemiology, oncology, genomics, human genetics, computer science, mathematics or a related field, or 5+ years experience working with genomic and clinical data
- Experience working with electronic health information and related software systems
- Experience in genetic analysis of complex disease and familiarity with common bioinformatics software and file formats
- Experience with statistical modeling, data mining and/or machine learning
- Experience with Python, R, or other modern programming language
- Excellent communications skills
- A collaborative mindset
- Experience with polygenic risk scores and population genetics
- Experience with clinical risk modeling and implementation
- Experience with version control (Git) and collaborative software development and testing
- Experience with AWS technical stack (EC2, S3, Redshift, etc.)
- Experience with Real World Evidence (RWE) and Real World Data (RWD) topics and techniques
- Experience with relational databases
- Record of meaningful scientific publications