Job summary
Job post source
This job is from a recruiting firm hiring for a separate company, as indicated by the company name TapTalent.ai which suggests a talent acquisition platform rather than the direct employer.
Job overview
The Computational Scientist – Human Genetics role involves analyzing large-scale genetic and genomic data to uncover disease biology insights, contributing to research publications, and supporting cross-functional teams.
Responsibilities and impact
The candidate will analyze genetic datasets, integrate multimodal biological data, manage data preprocessing and quality control, develop analytical pipelines, present findings internally, and contribute to publications.
Compensation and benefits
The position offers an hourly pay range of $26.95 to $61.95 and allows remote or hybrid work, with a fixed 12-month contract duration.
Experience and skills
Candidates should have a PhD or MS with significant experience in relevant fields, proficiency in R, Python, Bash, experience with GWAS and variant analyses, familiarity with biobank datasets and EHR/RWD, and skills in Git, parallel computing, and workflow tools; cardiovascular research experience is a plus.
Work environment and culture
The role supports remote or hybrid work styles, indicating flexibility in work environment.
Job location and travel
The job is based in South San Francisco, CA, with options for remote or hybrid work arrangements.
Unique job features
The job involves working with cutting-edge genetic and genomic datasets and advanced computational tools in a research-focused environment.
Company overview
TapTalent.ai is an AI-powered talent ecosystem that streamlines the recruitment process through automated multi-channel outreach and talent discovery. The company, backed by Iterative Capital and Salesforce Startup Programme, offers tools for effortless talent outreach, including auto-enrichment of contact details and integration with company databases. Founded by Dhruv Bhagat and Shubham Kumar, TapTalent.ai operates out of Singapore and employs 100-200 people. It is a product of Consultagora Solutions Pvt. Ltd. and focuses on enhancing hiring efficiency for modern recruiters.
How to land this job
Tailor your resume to highlight your expertise in analyzing large-scale genetic datasets like WGS and single-cell RNA/ATAC-Seq, emphasizing your experience in multimodal data integration to uncover disease biology insights.
Showcase proficiency in R, Python, Bash, and familiarity with workflow tools such as WDL or Nextflow, along with experience in managing data preprocessing, QC, and developing analytical pipelines, as these are key responsibilities.
Apply through multiple channels including TapTalent.ai’s official career page and LinkedIn to maximize your application’s visibility and reach.
Connect with professionals in the computational biology or human genetics divisions at TapTalent.ai on LinkedIn; use ice breakers like commenting on recent publications they contributed to or asking about their experience with specific biobank datasets such as UK Biobank or FinnGen.
Optimize your resume for ATS by incorporating keywords from the job description such as 'GWAS,' 'variant analyses,' 'biobank datasets,' 'parallel computing,' and 'workflow tools,' ensuring your resume passes automated screenings.
Leverage Jennie Johnson’s Power Apply feature to automate tailored applications across multiple platforms, identify relevant LinkedIn contacts for networking, and ensure your resume is optimized for ATS, freeing you to focus on preparing for interviews and further skill development.
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