Research Data Analyst
The Research Data Analyst supports collaborative research by integrating genomic, multi-omic, clinical, and EHR data to investigate the molecular basis of psychiatric and complex traits. Responsibilities include performing advanced statistical analyses, developing reproducible pipelines, managing high-dimensional datasets, and collaborating closely with investigators to design studies and prepare research outputs. This role requires strong skills in R, statistical modeling, and data curation within a hybrid work environment at Confidential Client.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Scientific & QA.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
The Research Data Analyst will support genomic and multi-omic research that integrates molecular data with clinical and EHR-derived phenotypes. Working under investigator direction, you will help design analyses, develop reproducible pipelines, and produce results for presentations and manuscripts.
- Perform statistical analyses of genomic and molecular datasets (PRS, association testing).
- Integrate genotype, transcriptome, DNA methylation, and clinical/EHR phenotype data to investigate molecular — clinical outcome relationships.
- Analyze high-dimensional transcriptomic and methylation datasets; run differential expression and association tests using R/Bioconductor (limma and related tools).
- Train genetically regulated expression (GReX) models and perform transcriptome-wide association studies (TWAS).
- Build and maintain reproducible analysis pipelines in R and/or Python.
- Curate, harmonize, and quality-control clinical and EHR phenotype data; produce analysis-ready datasets.
- Create visualizations, run statistical models, and document interpretation of results for collaborative teams.
- Maintain well-documented data products and analysis outputs to support reproducibility and publication.
Qualifications
Education & Experience
- Bachelor’s or Master’s degree in bioinformatics, biostatistics, computational biology, data science, statistics, genetics/genomics, or a related quantitative field required.
- Relevant research experience, internships, or coursework may substitute for formal experience (0–1 year typical for this level).
Technical Skills
- Proficiency in R for statistical analysis; experience with R/Bioconductor packages (limma, edgeR, DESeq2) preferred.
- Experience with Python is desirable for pipeline scripting and data engineering tasks.
- Familiarity with large, complex biomedical datasets (genomic, transcriptomic, methylomic).
- Knowledge of PRS, GWAS, TWAS/GReX analysis workflows is desirable.
- Experience working with clinical or EHR-derived phenotype data (curation, harmonization, QC) desirable.
- Strong data visualization, statistical modeling, and data quality-control skills.
- Excellent organizational skills and commitment to reproducible, documented analyses.
- Ability to collaborate with multidisciplinary teams of investigators, scientists, and clinicians.
Preferred / Nice-to-have
- Prior experience with GWAS/TWAS toolchains and PRS computation.
- Familiarity with common genomic data formats (VCF, BAM, FASTQ), annotation resources, and high-performance computing environments.
- Experience with workflow managers (Snakemake, Nextflow) or containerization (Docker/Singularity).
- Prior manuscript preparation or experience supporting presentations and publications.
Role Details
- Location: Belmont, CA (hybrid)
- Work location address: 115 Mill Street
- Employment type: Full-time, regular
- Scheduled weekly hours: 40
- Work shift: Day
- Pay range: $41,932.80 - $60,340.80 per year (base pay range provided by the client)
Careertakes works with the client to ensure pay and benefits are competitive and aligned with qualifications, experience, and internal pay practices.
Why Join
- Contribute to interdisciplinary research that links genomics and clinical outcomes.
- Gain hands-on experience with modern genomic analysis methods (PRS, TWAS, differential expression).
- Collaborate with investigators, researchers, and clinicians on projects leading to publications and presentations.
- Professional development and mentoring opportunities in a research-focused environment.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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