Lead Data Scientist in Statistical Genetics
2 weeks ago
About Optima Partners
Optima Partners is a leading professional services firm experiencing rapid growth and innovation. We are dedicated to advancing our capabilities in data science and statistical genetics, seeking exceptional talent to contribute to our cutting-edge solutions.
The Opportunity: Lead Data Scientist in Statistical Genetics
We are searching for a highly motivated and experienced Lead Data Scientist specializing in Statistical Genetics or Bioinformatics. This role will be pivotal in driving our genetic research initiatives and contributing to innovative solutions that enhance our services.
Key Responsibilities: Strategic Leadership (Lead Position Only)
- Develop and execute 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.
- Interpret results and establish tangible links between outcomes and methodologies 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, and heritability.
- Apply genetics causal inference methodologies such as fine-mapping, colocalization, and Mendelian randomization.
- Scientifically support ideation, design, development, and maintenance of 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 Skills & Experience
- Develop statistically grounded methodologies to arrive at 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 audiences.
- Effectively present research findings and insights to stakeholders.
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