Bioinformatics Scientist

Jobtailor; California (MO); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor is seeking a highly qualified bioinformatics scientist to advance ML models and NGS data analysis for oncology biomarker detection from cell-free DNA. You will work on assays, ML pipelines, and regulatory submissions in a collaborative, interdisciplinary team.

The role emphasizes translating research into production-scale pipelines, with collaboration across wet-lab scientists, medical directors, biostatisticians, software engineers, and product managers to deliver actionable clinical

Qualifications

• Must have completed a Ph.D. or a Master's with 3+ years of industry experience in Bioinformatics, Computational Biology, Cancer Biology, Genetics, Immunology, Molecular Biology, or Computer Science
• In-depth knowledge of tools and pipelines for processing, aligning, and analyzing multimodal NGS data, including epigenetics, DNA, and RNA
• Computational skills using Python and/or R, including data science and biological computing libraries
• Expertise with AWS or GCP, Docker, and workflow management tools such as Nextflow or Snakemake
• Scientific publications and/or contribution to successful industry product development
• Strong background in statistical modeling, predictive/prognostic algorithms, and machine learning techniques
• Effective communication and presentation skills
• Self-driven and able to work well in interdisciplinary teams

Responsibilities

• Develop, tune, and optimize novel assays, algorithms, machine learning and statistical models to analyze next-generation sequencing (NGS) and multimodal data for oncology biomarker detection from cell-free DNA
• Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation and longitudinal treatment response monitoring
• Improve molecular barcoding filtering strategies to distinguish low-frequency oncology biomarkers from sequencing artifacts
• Design and integrate machine learning classifiers and filtering logic to differentiate Clonal Hematopoiesis variants from tumor-derived variants
• Design and execute experiments evaluating assay analytical performance
• Support regulatory documentation for CAP/CLIA, New York State, FDA, and MolDx submissions
• Collaborate with wet-lab assay development scientists, medical directors, clinical scientists, biostatisticians, software engineers, and product managers
• Translate research into clinically actionable insights and production-scale pipelines

Skills

Machine Learning

Data Analysis

Python

R

Statistical Modeling

Bioinformatics

Computational Biology

Molecular Biology

Cancer Biology

Genetics

Education

PhD or Master's with 3+ years industry experience

Tools

AWS

GCP

Docker

Nextflow

Snakemake

Job description

Professional Responsibilities

• Develop, tune, and optimize novel assays, algorithms, machine learning and statistical models to analyze next-generation sequencing (NGS) and multimodal data for oncology biomarker detection from cell-free DNA
• Develop and refine machine learning models for cell-free circulating tumor DNA fraction estimation and longitudinal treatment response monitoring
• Improve molecular barcoding filtering strategies to distinguish low-frequency oncology biomarkers from sequencing artifacts
• Design and integrate machine learning classifiers and filtering logic to differentiate Clonal Hematopoiesis variants from tumor-derived variants
• Design and execute experiments evaluating assay analytical performance
• Support regulatory documentation for CAP/CLIA, New York State, FDA, and MolDx submissions
• Collaborate with wet-lab assay development scientists, medical directors, clinical scientists, biostatisticians, software engineers, and product managers
• Translate research into clinically actionable insights and production-scale pipelines

Requirements

• Must have completed a Ph.D. or a Master's with 3+ years of industry experience in Bioinformatics, Computational Biology, Cancer Biology, Genetics, Immunology, Molecular Biology, or Computer Science
• In-depth knowledge of tools and pipelines for processing, aligning, and analyzing multimodal NGS data, including epigenetics, DNA, and RNA
• Computational skills using Python and/or R, including data science and biological computing libraries
• Expertise with AWS or GCP, Docker, and workflow management tools such as Nextflow or Snakemake
• Scientific publications and/or contribution to successful industry product development
• Strong background in statistical modeling, predictive/prognostic algorithms, and machine learning techniques
• Effective communication and presentation skills
• Self-driven and able to work well in interdisciplinary teams

Core Competencies

Demonstrates expertise in developing and optimizing machine learning models for analyzing next-generation sequencing data, with a strong focus on oncology biomarker detection and regulatory compliance. Proficient in translating complex research into actionable clinical insights and production-scale pipelines.

Highest-signal resume keywords

• Ph.D. Or Master's In Bioinformatics
• Machine Learning Model Development
• Next-Generation Sequencing Data Analysis
• Statistical Modeling And Predictive Algorithms
• AWS Or GCP Expertise

ATS Optimization Keywords

Hard Skills

• Machine Learning
• Statistical Modeling
• Data Analysis
• Bioinformatics
• Computational Biology
• Python
• R
• Molecular Biology
• Cancer Biology
• Genetics

Soft Skills

• Effective Communication
• Presentation Skills
• Self-Driven
• Team Collaboration

Industry Keywords

• Oncology Biomarker Detection
• Cell-Free DNA
• Clonal Hematopoiesis
• Regulatory Documentation
• CAP/CLIA
• FDA
• MolDx
• Multimodal Data
• Assay Analytical Performance
• Scientific Publications

Tools & Technologies

• AWS
• GCP
• Docker
• Nextflow
• Snakemake