Hybrid Prenatal Genomics Reporting CLS

BillionToOne Inc.; Union City (CA); Hybrid; USD 74,000 - 105,000; Part time

Benefits offered by this job

Daily on-site lunches

State-of-the-art gym

On-site EV charging

Job summary

BillionToOne Inc. is seeking a Reporting Clinical Laboratory Scientist (contractor) in Union City, CA. The role emphasizes high-complexity data analysis, interpretation of molecular diagnostics, and timely reporting under CLIA/CAP guidance.

The RCLS will independently run validated bioinformatics pipelines, review results, and collaborate with Bioinformatics and Laboratory Directors. A strong emphasis on technical leadership, QA, and process improvement is required, with a hybrid model (roughly

Qualifications

• Active California CLS license (or CGMBS) or equivalent.
• Bachelor's degree or higher in a related scientific field per licensure.
• Experience in high-complexity molecular diagnostics or clinical genomics.
• Experience with sequencing data analysis and QC metrics.

Responsibilities

• Analyze and interpret clinical genomic data from patient samples.
• Review and release clinical reports per regulatory requirements.
• Troubleshoot analytical discrepancies with cross-functional teams.
• Manage daily priorities and ensure timely reporting.

Skills

NGS data analysis

Bioinformatics

Analytical thinking

Written & verbal comms

Problem solving

Independent judgment

Education

Bachelor's degree or higher in Biomedical Laboratory Sciences

Tools

Atlassian Suite

Google Workspace

Microsoft Office

LIMS / Laboratory Data Management Systems

Job description

BillionToOne Inc. is seeking a Reporting Clinical Laboratory Scientist (contractor) in Union City, CA. The role emphasizes high-complexity data analysis, interpretation of molecular diagnostics, and timely reporting under CLIA/CAP guidance.

The RCLS will independently run validated bioinformatics pipelines, review results, and collaborate with Bioinformatics and Laboratory Directors. A strong emphasis on technical leadership, QA, and process improvement is required, with a hybrid model (roughly