Genomic Data Scientist

TN United Kingdom; London; On-site; GBP 40,000 - 80,000; Full time

Job summary

A forward-thinking company is looking for a Genomic Data Scientist to enhance their Bioinformatics Consulting team. This role involves working on innovative genome analysis projects aimed at tackling rare and complex diseases. You will collaborate with multidisciplinary teams to leverage extensive datasets for drug target identification and biomarker discovery. Your expertise will be crucial in developing tools and pipelines for custom analyses, ensuring high-quality reporting and documentation. If you are passionate about genomics and want to make a significant impact in the field, this opportunity is perfect for you.

Qualifications

• Strong programming skills in R and Python with a background in statistical genetics.
• Experience with whole genome sequencing data and human genetics contexts.

Responsibilities

• Preparing data for analysis through quality control and functional annotation.
• Performing custom computational analyses on whole genome sequencing and omics data.

Skills

R Programming

Python Programming

Statistical Genetics

Whole Genome Sequencing

Human Disease Genetics

Omics Data Analysis

Genetic Association Testing

Population Genetics

Pharmacogenomics

Attention to Detail

Tools

Nextflow

Cloud Environments

Job description

We are seeking a Genomic Data Scientist to join our Bioinformatics Consulting team to work on genome analysis and interpretation projects, focusing on rare or complex diseases, in collaboration with external researchers and industrial partners.

In this role, you will work within multidisciplinary teams to develop and execute cutting-edge projects leveraging Genomics England datasets to address research goals such as drug target identification, biomarker discovery, diagnostic development, and patient stratification.

You will contribute to the scoping, implementation, and application of state-of-the-art approaches for analyzing genomic and other omics data, both in leading and supporting roles. As an expert user of our datasets and environment, you will develop and refine tools and pipelines for custom analyses, generate new data, and contribute to high-quality reports and documentation.

Everyday responsibilities include:

1. Preparing data for analysis through quality control, functional annotation, aggregation, and harmonization across datasets.
2. Planning and supporting analyses to meet project objectives, providing support to teams and collaborators, and serving as a reference point for genomic datasets and analytical approaches.
3. Performing custom computational analyses on whole genome sequencing and other omics data, such as GWAS, aggregate variant testing, meta-analysis, differential abundance, fine-mapping, and Mendelian Randomization (MR).
4. Researching scientific literature to identify new approaches for processing and analyzing genomics and multi-omics data, benchmarking, and improving tools.
5. Contributing to the publication and dissemination of findings via scientific papers, white papers, and conference presentations.

Skills and Experience for Success:

• Strong programming skills in R and Python, with a solid background in statistical genetics.
• Experience with whole genome sequencing data in human genetics contexts.
• A strong background in human disease genetics, especially in rare or complex diseases, demonstrated through publications or industry experience.
• Experience with at least one additional omics modality (e.g., long-read sequencing, single-cell transcriptomics, proteomics, metabolomics).
• Proven expertise in areas like genetic association testing, population genetics, pharmacogenomics, rare disease genomics, structural variation analysis, and working with complex regions like HLA/KIR/PGx.
• Experience working in cloud environments, building containers, and running pipelines in Nextflow.
• Ability to communicate effectively with stakeholders from diverse backgrounds and understanding of clinical and phenotypic data management, including patient data sensitivities.
• Excellent interpersonal skills, attention to detail, self-motivation, and a collaborative, delivery-focused mindset.