Senior Data Scientist, Cancer Genomics & ML

BioSpace; Menlo Park (CA); Hybrid; USD 156,000 - 187,000; Full time

Benefits offered by this job

Flexible time-off

401(k) employer match

Medical, dental, and vision coverage

Mindfulness programs

Job summary

GRAIL is seeking a Senior Data Scientist to join the Computational Biology team in the Bay Area. You will analyze population-scale genomic data from our clinical studies to model interactions between technical, biological and clinical factors that affect test performance and guide future innovations.

You will develop state-of-the-art methods to monitor a multi-cancer classifier in production and help ensure high performance as products scale to large adoption.

Qualifications

• Ph.D. in Bioinformatics, Data Science, Computational Biology, Physics, Bioengineering, Cancer Genomics, Statistics, Biochemistry or related field with 2+ years of experience.
• Large-scale omics datasets experience in R or Python.
• Experience with NGS data processing, statistical modeling, and ML in a clinical setting.
• Excellent communication and collaboration across interdisciplinary teams.
• Detail-oriented and rigorous scientific work.

Responsibilities

• Analyze high-dimensional genomic datasets to identify trends and communicate findings across teams.
• Build predictive models integrating biology, epigenetics and statistics to assess test performance.
• Collaborate with ML, software, clinical, and product teams across Grail.
• Create and communicate rigorous scientific analyses.

Skills

Omics data

R/Python

Statistical modeling

Effective communicator

Interdisciplinary teamwork

Education

PhD in relevant field

Tools

R

Python

NGS data processing

Linux

Git

Job description

GRAIL is seeking a Senior Data Scientist to join the Computational Biology team in the Bay Area. You will analyze population-scale genomic data from our clinical studies to model interactions between technical, biological and clinical factors that affect test performance and guide future innovations.

You will develop state-of-the-art methods to monitor a multi-cancer classifier in production and help ensure high performance as products scale to large adoption.