Job
Description
Role: Data Scientists - Computational Scientist / Applied Mathematician Location: Bangalore Must Have: MSc/PhD in Physics, Stats, Math, Comp Bio, CS, etc. Strong Python + Jupyter skills Experience with real-world biological data Eager to learn biology & make real patient impact Bonus: Genomics, sequencing tech, cloud (AWS/GCP), Rust/C++, Snakemake, ML models Work with biologists, chemists & ML scientists to analyze experiments & build predictive tools. About Role You have strong mathematical foundations and a passion for understanding & analyzing data. You have a solid understanding of how to analyze noisy, real-world, data. In addition to a strong background in statistics, you are also capable of programming a computer to perform data analysis tasks. You want to impact people by treating genetic diseases and are capable of learning biology that is crucial to the data analysis task. You enjoy close-knit teamwork and a highly interdisciplinary intellectual environment where you will work side-by-side with both computational and bench scientists. You continually learn and challenge yourself with scientific pursuits. You take pride in rigorous pursuit of science. Required Qualifications MSc or PhD in a quantitative discipline such as physics, statistics, economics, applied mathematics, computer science, computation genomics / biology or related field Familiarity with analyzing real world data and quantifying uncertainty Good understanding of Python is a required, knowledge of Rust / C++ are nice to have Very comfortable with Juptyer ecosystem Ability to independently master unfamiliar topics, especially in biological sciences and data analysis Desire to make a difference to patients with rare disease Helpful Qualifications Strong foundation in algorithms of scientific computing: steepest descent, Metropolis-Hastings, Runge-Kutta, Krylov space methods, etc Fluent and comfortable working across local and cloud environments and tools (AWS, GCP, kubernetes, docker) Understanding of sequencing technologies (Illumina, PacBio, Oxford Nanopore) Knowledge of standard software tools in transcriptomics, genomics, NGS assays & biological data analysis Understanding of Linux, make, snakemake, git, etc. Exposure in distributed computing (Spark, Dask etc.)
