Senior Scientist – Bioinformatics, Computational Biology, Proteomics

Jobtailor; South San Francisco (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Amgen is seeking a highly skilled computational biologist for the Discovery Proteomics Group in South San Francisco. You will develop data infrastructure, run proteomics analyses, and collaborate with scientists across functions to advance biomarker discovery and target evaluation.

The role emphasizes large-scale data integration, reproducible workflows, and practical implementation of computational pipelines.

Qualifications

• Doctorate degree OR Master’s degree and 3 years of scientific experience OR Bachelor’s degree and 5 years of scientific experience
• PhD in Computational Biology, Bioinformatics, Statistics, Proteomics, or Biology preferred
• Expertise in large-scale quantitative proteomics and other omics data analysis
• Fluency in Python, R, and SQL
• Familiarity with analytic techniques/packages for statistical analysis, data processing, data ingestion, data visualization, and basic machine learning
• Working knowledge of Unix/Linux and AWS cloud computing environments
• Experience in version control, Docker containers, coding project management, reproducible data analysis, and documentation
• Experience in meta-analysis with publicly available large proteomics studies is a plus
• Strong background in biology or chemistry, especially human diseases in Immunology, Oncology, Inflammation, and Cardiometabolic Disease
• Proven track record of independent critical thinking and scientific achievement
• Strong verbal and written skills
• Ability to work independently and in small teams
• Willingness and ability to collaborate across scientific disciplines and cross-functional teams

Responsibilities

• Develop computational tools and data infrastructure for the Discovery Proteomics Group
• Conduct statistical analysis, data ingestion, database and tool development, and computational pipeline implementation for proteomics data
• Support biomarker discovery, target evaluation, experimental design, and mechanism-of-action studies
• Develop and implement data analysis, management, and visualization strategies for complex mass spectrometry and other technology datasets
• Work closely with scientists across functions and therapeutic areas
• Deliver and present analysis results to key stakeholders
• Collaborate across genomic and proteomic platforms for data integration and mining
• Utilize available external resources where appropriate
• Enable Amgen’s preclinical pipeline through innovative technologies and technical expertise

Skills

PhD in Computational Biology

Python

R

SQL

Docker

Unix/Linux

AWS

Statistics

Machine Learning

Data Visualization

Education

PhD in Computational Biology

Tools

Docker Containers

Version Control Systems

Cloud Computing

Job description

Responsibilities

• Develop computational tools and data infrastructure for the Discovery Proteomics Group
• Conduct statistical analysis, data ingestion, database and tool development, and computational pipeline implementation for proteomics data
• Support biomarker discovery, target evaluation, experimental design, and mechanism-of-action studies
• Develop and implement data analysis, management, and visualization strategies for complex mass spectrometry and other technology datasets
• Work closely with scientists across functions and therapeutic areas
• Deliver and present analysis results to key stakeholders
• Collaborate across genomic and proteomic platforms for data integration and mining
• Utilize available external resources where appropriate
• Enable Amgen’s preclinical pipeline through innovative technologies and technical expertise

Requirements

• Doctorate degree OR Master’s degree and 3 years of scientific experience OR Bachelor’s degree and 5 years of scientific experience
• PhD in Computational Biology, Bioinformatics, Statistics, Proteomics, or Biology preferred
• Expertise in large-scale quantitative proteomics and other omics data analysis
• Fluency in Python, R, and SQL
• Familiarity with analytic techniques/packages for statistical analysis, data processing, data ingestion, data visualization, and basic machine learning
• Working knowledge of Unix/Linux and AWS cloud computing environments
• Experience in version control, Docker containers, coding project management, reproducible data analysis, and documentation
• Experience in meta-analysis with publicly available large proteomics studies is a plus
• Strong background in biology or chemistry, especially human diseases in Immunology, Oncology, Inflammation, and Cardiometabolic Disease
• Proven track record of independent critical thinking and scientific achievement
• Strong verbal and written skills
• Ability to work independently and in small teams
• Willingness and ability to collaborate across scientific disciplines and cross-functional teams

Core Competencies

Demonstrates expertise in computational biology and proteomics, with strong capabilities in data analysis, management, and visualization. Proficient in Python, R, and SQL, with a solid understanding of statistical analysis and machine learning techniques.

Highest-signal resume keywords

• PhD In Computational Biology
• Large-Scale Quantitative Proteomics Analysis
• Fluency In Python, R, And SQL
• Experience In Docker Containers And Version Control
• Strong Background In Biology Or Chemistry

Hard Skills

• Statistical Analysis
• Data Ingestion
• Database Development
• Computational Pipeline Implementation
• Data Visualization
• Analytic Techniques
• Machine Learning
• Reproducible Data Analysis
• Meta-Analysis
• Data Management

Soft Skills

• Independent Critical Thinking
• Strong Verbal Communication
• Strong Written Communication
• Collaboration Across Disciplines
• Ability To Work In Small Teams

Industry Keywords

• Proteomics
• Biomarker Discovery
• Target Evaluation
• Experimental Design
• Human Diseases
• Immunology
• Oncology
• Inflammation
• Cardiometabolic Disease

Tools & Technologies

• Unix/Linux
• AWS Cloud Computing
• Docker
• Version Control Systems
• Analytic Packages