Principal Scientist, Translational Genetics

Cytokinetics; South San Francisco (CA); On-site; USD 203,000 - 236,000; Full time

Job summary

Cytokinetics is seeking a Principal Scientist, Translational Genetics to lead analysis of large-scale genetic datasets and identify therapeutic targets for cardiovascular and muscle diseases.

The role emphasizes statistical genetics, AI/ML, data management, and collaboration with biologists and clinicians to translate discoveries into preclinical and clinical research.

Qualifications

• Ph.D. in Statistical Genetics, Human Genetics, Bioinformatics, Computational Biology or a related field.
• Expertise in statistical genetics, genomics, and translational data analysis.
• Experience with cloud computing platforms and biobank research tools.
• Publications in statistical genetics or cardiovascular genetics preferred.

Responsibilities

• Perform GWAS, fine-mapping, and large-scale genetic analyses.
• Integrate multi-omics data to identify causal variants and pathways.
• Develop models to predict disease risk and treatment response.
• Design AI/ML approaches for imaging-derived phenotyping.
• Collaborate with cross-functional teams and translate findings to preclinical and clinical studies.

Skills

Statistical genetics

Genomics

Bioinformatics

AI/ML methods

Data analysis

Education

Ph.D. in Statistical Genetics

Tools

R

Python

PLINK

Hail

Job description

Cytokineticsis a specialty cardiovascular biopharmaceutical company, building on its over 25 years of pioneering scientific innovations in muscle biology, and advancing a pipeline of potential new medicines for patients suffering from diseases of cardiac muscle dysfunction.

At Cytokinetics, each team member plays an integral part in advancing our mission to improve the lives of patients. We are seeking tenacious, compassionate, and collaborative individuals who are driven to make a positive impact.

We are seeking a highly motivated and skilled Principal Scientist, Translational Genetics to join our growing team. The successful candidate will play a critical role in analyzing large-scale genetic and genomic datasets to identify and select therapeutic targets for cardiovascular and muscle diseases. This position requires a strong foundation in statistical genetics, bioinformatics, AI/ML methods, genomics and a passion for translating genetic insights into clinical applications.

Responsibilities

Data Analysis

• Perform genome-wide association studies (GWAS), fine-mapping, and other statistical genetics analyses using large-scale genomic datasets (e.g., UK Biobank, All of Us, FinnGen, etc.).
• Analyze and integrate multi-omics data (genomics, transcriptomics, proteomics, metabolomics) to identify causal variants and pathways associated with cardiovascular diseases.
• Develop and apply statistical models to predict disease risk and treatment response based on genetic and clinical data.
• Design and evaluate AI/ML methods for large-scale imaging-derived phenotyping (e.g., cardiac MRI, DEXA)
• Conduct Mendelian randomization studies to infer causal relationships between genetic variants and cardiovascular traits.

Target Identification and Validation

• Identify and prioritize genetic targets for therapeutic intervention based on statistical and functional evidence.
• Contribute to the design and analysis of genetic studies to validate drug targets and biomarkers.
• Collaborate with experimental biologists and clinicians to translate genetic findings into preclinical and clinical research.

Bioinformatics and Data Management

• Develop and maintain bioinformatics pipelines for processing and analyzing genomic and electronic health records (EHR) data.
• Manage and curate large-scale genetic and clinical datasets.
• Utilize and develop statistical software and tools for data analysis and visualization (e.g., R, Python, PLINK, Hail).

Collaboration and Communication

• Collaborate with cross-functional teams, including biologists, clinicians, and computational scientists.
• Present research findings at internal meetings, scientific conferences, and in peer-reviewed publications.
• Contribute to the preparation of regulatory documents and grant applications.
• Maintain detailed and organized records of all analyses.

Qualifications

• Education: Ph.D. in Statistical Genetics, Human Genetics, Bioinformatics, Computational Biology or a related field with
• Experience:
• Skills:

Preferred Qualifications

• Experience with cloud computing platforms (e.g., AWS, Google Cloud) and biobank research analysis platforms (e.g., DNAnexus RAP, All of Us Workbench)
• Experience with machine learning and deep learning methods, and strong interest in applying these methods to biological problems
• Experience with multidimensional and longitudinal data analysis in biology or medicine
• Publications in peer-reviewed journals related to statistical genetics and cardiovascular disease.

Pay Range

In the U.S., the hiring pay range for fully qualified candidates is $202,500.00 - $236,250.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors.

Our employees come from different backgrounds, and we celebrate those differences. We are looking for the best candidates for our open roles, but do not expect applicants to meet every qualification in order to be considered. If you are excited about what you could accomplish at Cytokinetics and believe you can add value to our team, we would love to hear from you.

Our passion is anchored in robust scientific thinking, grounded in integrity and critical thinking. We keep the patient front and center in all we do – all actions and decisions are in service of the patient and their caregivers. We champion integrity, ethics, doing the right thing, and being our best selves.

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Cytokinetics is an Equal Opportunity Employer