Bioinformatics Engineer II - Genomics Algorithm Development


We are seeking a creative developer with a strong statistics and machine learning background to join Sloan Kettering Institute’s Single Cell Research Initiative (SCRI). The team’s goal is to develop cutting-edge algorithms to interpret the flood of data emerging from single-cell technologies in order to explore questions in tumor heterogeneity, metastasis and the tumor-immune environment. If you would rather apply your superb programming and analytical skills towards a cancer cure than to finance and shopping carts, our dynamic multi-disciplinary team is the place for you.

SCRI is directed by computational biologist Dr. Dana Pe’er, a pioneer with a strong track record of developing new conceptual approaches and widely used tools in the single-cell analysis field. We collect big biological data, primarily from multi-dimensional single-cell technologies such as single-cell RNA sequencing and high-parameter imaging. You will develop and implement algorithms that process, integrate and visualize the multiple data types, allowing data scientists, biologists and clinicians to interact with and interpret the data. A key focus is the single-cell profiling of patient samples, with the goal of improving immunotherapy and precision medicine. Join us if you are an innovative thinker and want to make an impact!

As a Bioinformatics Software Engineer, you will:

  • Design and develop algorithms and software to process, normalize, organize, visualize and interpret data from multiple modalities, including from single-cell and imaging technologies
  • Design and implement novel machine learning algorithms to integrate genomics data collected from clinical cohorts
  • Implement new features, maintain and test existing SCRI code infrastructure
  • Evaluate and compare best practices for processing and analyzing different data types
  • Provide consultation, guidance and training to research scientists using SCRI tools


  • Bachelor’s or Master’s degree with strong machine learning or stats components, and 3+ years of programming experience; or PhD in math, physics or computer science; or equivalent experience
  • Bioinformatics/genomics experience and familiarity with common concepts, terminologies and software currently used in the field
  • Experience designing large software tools and writing efficient code
  • Proficiency in the testing process; ability to debug and modify code and use Git workflows
  • Analytical, reasoning, mathematical and problem-solving skills to develop algorithms
  • Advanced knowledge of algorithms and statistics
  • Proficiency in Python (including building distributable Python modules)
  • Proficiency working in cloud and HPC environments

To apply, please visit the MSK career site.