Optima Partners is a leading professional services firm experiencing rapid growth and innovation. As part of our expansion, we are dedicated to advancing our capabilities in data science and statistical genetics. We are seeking an exceptional Lead Data Scientist specialising in Statistical Genetics or bioinformatics to join our team. This role will be pivotal in driving our genetic research initiatives and contributing to cutting-edge solutions that enhance our services.

Key Responsibilities

Strategic Leadership (only for the Lead position)

• Lead the development and execution of data science strategies focused on statistical genetics, bioinformatics and computational biology.
• Collaborate with cross-functional teams to integrate genetic data insights into broader business strategies.
• Provide thought leadership in the application of statistical genetics to solve complex biological and medical problems.

Research Development

• Design and conduct advanced statistical analyses of large-scale genetic and genomic datasets.
• Ability to interpret the results and find tangible link between the outcomes and the methodology applied.
• Develop and validate predictive models to understand genetic contributions to complex traits and diseases.
• Stay abreast of the latest advancements in statistical genetics and bioinformatics, incorporating relevant techniques into ongoing projects.

Technical Expertise

Required

• Apply statistical genetics methodologies such as genome-wide association studies (GWAS), meta-analysis, polygenic risk scoring, heritability.
• Apply genetics causal inference methodologies such as finemapping, colocalization and Mendelian randomisation.
• Scientifically support ideation, design, development and maintenance of the large-scale pipelines and workflows.
• Ensure robust data processing pipelines and workflows for handling large-scale genomic data.
• Familiarity with target validation approaches such as ontology pathway enrichment, gene and protein annotations, disease-phenotype associations.

Preferred

• Develop statistically grounded methodologies to arrive to practical solutions.
• Data Management Compliance
• Ensure the integrity, security, and confidentiality of genetic data in compliance with relevant regulations.
• Implement and maintain high standards for data quality and reproducibility in research findings.

Communication Reporting

• Communicate complex statistical genetic concepts and findings to non-technical stakeholders.
• Communicate and align with engineering and product teams and work towards achieving common understanding of needs and requirements.
• Prepare and present scientific publications, reports, and presentations to both internal and external audiences.

Skills Experience

• PhD (or Masters degree with extensive experience) in quantitative discipline such as Statistical Genetics, Bioinformatics, Computational Biology, or a related field.
• Minimum of 5 years of experience (for Lead position) or at least 3 years of experience (for Senior position) in statistical genetics or a closely related discipline.
• Strong programming skills in languages such as R, Python, and experience with relevant bioinformatics tools and databases.
• Extensive experience with large-scale genomic datasets (e.g., Open Target Genetics, GWAS-/eQTL-Cat) and biobanks (e.g., UKBiobank, FinnGen)
• Experience in target validation procedures such as variant annotations (VEP), GO enrichment, pathway enrichment, PPIs.
• Experience in utilizing and understanding of on-prem and/or cloud high-performance computing environments.
• Experience working with at least one cloud platform (Azure, GCP, Amazon AWS).
• Experience working with bioinformatics tools CLI/APIs (e.g. PLINK, bcftools, GATK, etc.)
• Proven track record of accomplishment of conducting and publishing high-quality research in statistical genetics.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Effective communication skills with the ability to convey complex scientific concepts to a diverse audience.

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