Scientist, Genetic Epidemiology

Mirador is a next-generation precision medicine company focused on immunology and inflammation. The company’s Mirador360 _^TM precision development engine leverages the latest advances in human genetics and cutting-edge data science to rapidly advance new precision medicines for patients living with chronic immune-mediated inflammatory and fibrotic diseases. Launched in 2024, Mirador has raised over $400 million from leading life sciences investors and is based in San Diego, CA.

Summary

We are seeking a talented genetic epidemiology scientist to join our precision medicine group. In this role, the successful candidate will design and apply statistical genetic and epidemiological methods to prioritize novel drug targets, enable patient enrichment strategies, and guide pre-clinical drug development decisions. A key focus of this role will be to integrate genetic, multiomics, and longitudinal clinical data in patient and population cohort studies to evaluate patient stratification and predict treatment response across subsets of immune-mediated diseases.

This position involves fostering collaborative partnerships with internal and external experts in data science, computational biology, data curation, disease biology, and clinical research. Together, you will design, implement, and refine genetic epidemiological analyses to deepen our understanding of the etiology of human diseases and optimize clinical trial design.

Responsibilities

• Use innovative genetic epidemiological analysis methods to generate insights about human disease. Approaches to be employed include longitudinal data analysis, prediction performance evaluation, Mendelian randomization, polygenic risk score modelling, and meta-analysis to identify key factors driving disease progression, severity and/or trajectory.
• Deep characterization of patient sub-populations utilizing longitudinal health record data, genetic, and multiomics data to provide insight into disease biology and treatment response.
• Critically review and provide input on analysis plans, results, and summaries to ensure they are accurate and reliable. Identify potential problems and propose remedies or refinements.
• Provide critical evaluation of real-world data sets to assess data content and quality and applicability for relevant use cases.
• Coordinate with team members or contractors to execute on key project objectives within pre-specified timelines.

Experience and Qualifications

• PhD in Statistical Genetics, Human Genetics, Genetic Epidemiology, Computational Biology/Bioinformatics, Bioengineering, Computer Science, or a related field.
• 2 or more years of relevant biotech and/or pharmaceutical industry experience; would also consider relevant academic experience.
• Strong track record of applying genetic epidemiology approaches to assess patient stratification and clinical trial design, demonstrated through peer-review publications or regulatory submissions.
• Demonstrated ability to analyze next generation sequencing data including SNP genotyping, Whole Genome Sequencing and Whole Exome Sequencing. Knowledge of human genetic association analyses and approaches, understanding of epidemiological study design, approaches for assessing shared genetic risks across phenotypes, and the use of genetic information in assessing disease risk and causal relationships.
• Experience working with multiomics data including proteomic, metabolomic, bulk or single cell RNA-seq to quantify disease risk or progression.
• Experience working with controlled access data from public repositories such as dbGaP and UK Biobank accessed internally or through trusted research environments.
• Experience analyzing longitudinal data in electronic health records including survival analysis and mixed effects models.
• Proficiency in R or Python is required (proficiency in both is preferred).
• Understanding of strategies and methods for genotype imputation, haplotyping, relationship inference and/or polygenic risk score estimation. Experience with multiple tools for large scale genetic analyses (e.g., PLINK, EPACTS, SAIGE, minimac, Hail, METAL/RAREMETAL).
• Experience conducting genetic epidemiologic analyses in one of the following phenotype areas: IBD, quantitative traits, inflammatory and immune-mediated disease, or drug response, preferred.
• Proficiency with Unix-based systems.
• Experience with source version control (e.g., Git) and cloud computing environments and tools (e.g., AWS, Azure, Docker) is a plus.

Skills and Abilities

• Highly collaborative working style and ability to adapt in a fast paced, rapidly developing environment with a diverse team of colleagues.
• Ability to work with general direction to meet objectives and timelines, adapting to changes and priorities.
• Bring innovative thinking to large-scale genetic studies and analysis.
• Have a strong work ethic and is proactive in providing solutions to foster scientific collaborations and drive projects forward.
• Have outstanding communication skills to summarize and present new statistical methods and concepts and the results of human genetic studies to a variety of technical audiences, ranging from specialists in statistical genetics and computation to specialists in biology, drug design and medicine.
• Is a motivated teammate with a desire to pursue genetic discovery in a multi-disciplinary environment.

The expected base pay range for this position is $125,000 - $165,000 plus bonus, equity, and comprehensive benefits. The base pay range reflects the target range for this position, but individual pay will be determined by additional factors such as job-related skills, experience and relevant education or training. This range may be modified in the future.

 

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