Computational Scientist

The Fountain Group; South San Francisco (CA); Hybrid; USD 34,000 - 76,000; Full time

Job summary

The Fountain Group is seeking a Computational Scientist – Human Genetics for a Remote/Hybrid role in the US. You will analyze large-scale genetic, genomic, and clinical datasets and develop computational workflows to interpret complex biology.

Responsibilities include applying ML methods, preparing datasets, documenting analyses and code, and presenting findings. Requires PhD or MS with relevant experience; proficiency in R and Python; GWAS, scRNA-Seq, scATAC-Seq, and SLURM experience preferred.

Qualifications

• PhD or equivalent in a relevant field with strong genetics background.
• Experience with large-scale genetic/genomic data analysis.
• Proficiency in GWAS and association analyses.
• Experience with RNA-Seq and single-cell data.
• Strong programming in R and Python; familiarity with HPC environments.

Responsibilities

• Develop computational workflows for human genetics data.
• Apply machine learning methods to omics datasets.
• Prepare datasets and document analyses and code.
• Present scientific findings to stakeholders.

Skills

Genetic data analysis

GWAS

RNA-Seq analysis

Single-cell analysis

Multimodal data integration

R programming

Python programming

Shell scripting

Git version control

HPC environments SLURM

Minimal supervision

Education

PhD in Statistical Genetics/Related Field

Master’s degree with relevant experience

Tools

SLURM

Git

R

Python

Job description

The Fountain Group is currently seeking a Computational Scientist for a prominent client of ours. This position is located in Remote / Hybrid (South San Francisco, CA). Details for the position are as follows:

Job Title: Computational Scientist – Human Genetics

Location: Remote / Hybrid – US-friendly time zone
Pay Rate: $25.23–$54.95/hr
Duration: 1 Year Contract

Job Description

Computational Scientist supporting Human Genetics research through analysis and integration of large-scale genetic, genomic, and clinical datasets. The role will develop computational and statistical approaches to interpret human biological data, including whole genome sequencing, single-cell sequencing, imaging, and multimodal datasets. Responsibilities include developing analytical workflows, applying machine learning methods, preparing datasets, documenting analyses and code, and presenting scientific findings.

Education

• PhD in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or related field.

• Master’s degree with significant relevant experience may be considered.

Required Skills

• Hands-on experience with large-scale genetic/genomic data analysis.

• Genetic epidemiology and statistical genetics principles.

• GWAS and association analysis using array- and sequence-based human genetic data.

• RNA-Seq analysis and differential gene expression.

• Single-cell data analysis, including scRNA-Seq and/or scATAC-Seq.

• Integration of genetic, genomic, molecular, and clinical data for multimodal analysis.

• R and Python programming.

• Shell scripting.

• Git version control.

• High-performance computing environments, including SLURM.

• Experience analyzing large biological datasets with minimal supervision.

Preferred Skills

• Whole genome sequencing (WGS) analysis.

• Proteomic data analysis.

• Multimodal data integration methods.

• Machine learning for imaging and omics data.

• Experience integrating imaging and molecular datasets.

• C++ familiarity.

• Experience with clinical trial, high-throughput screening, or public genomic datasets.