Description review
Genomics Researcher - Fully Remote | Upto $100/hr
mercor · United Kingdom · back to the listing
HR standards
77/100
solid
Title ↔ description
45/100
poor
Reads as
Data Scientist
80% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
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What the listing never says
- 19 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Bioinformatics & Computational Single-Cell Genomics Expert
Type:Contract
Compensation:$70–$100/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
• Design challenging computational problems to test AI systems using real scientific software.
• Create problems requiring skilled use of specialized software like scanpy, scvelo, squidpy, and gudhi.
• Evaluate and refine problems through testing loops against state-of-the-art AI models.
• Develop problems that require strategic planning for experiments and queries to uncover hidden data.
• Work independently to refine problem designs based on feedback and improve AI model performance.
Qualifications
Must-Have
• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
• Proven proficiency with scientific software libraries through research publications or professional work.
• Strong Python skills for writing problem setups and solution validators.
• Ability to work independently and refine designs based on feedback.
• Comfortable in a Linux/terminal environment with remote compute sandboxes.
Preferred
• Experience across multiple listed domains or tools.
• Familiarity with benchmark or evaluation design.
• Background in scientific teaching or exam/problem-set design.
• Experience with computational reproducibility and containerized environments.
Application Process (Takes 20–30 mins to complete)
• Upload resume
• AI interview based on your resume
• Submit form
Resources & Support
• For details about the interview process and platform information, please check:
• For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Bioinformatics & Computational Single-Cell Genomics Expert
Type:Contract
Compensation:$70–$100/hour
Location:Remote
Commitment:15–20 hours/week
Role Responsibilities
• Design challenging computational problems to test AI systems using real scientific software.
• Create problems requiring skilled use of specialized software like scanpy, scvelo, squidpy, and gudhi.
• Evaluate and refine problems through testing loops against state-of-the-art AI models.
• Develop problems that require strategic planning for experiments and queries to uncover hidden data.
• Work independently to refine problem designs based on feedback and improve AI model performance.
Qualifications
Must-Have
• Graduate-level training in a relevant STEM field (MS, PhD, or equivalent research experience).
• Proven proficiency with scientific software libraries through research publications or professional work.
• Strong Python skills for writing problem setups and solution validators.
• Ability to work independently and refine designs based on feedback.
• Comfortable in a Linux/terminal environment with remote compute sandboxes.
Preferred
• Experience across multiple listed domains or tools.
• Familiarity with benchmark or evaluation design.
• Background in scientific teaching or exam/problem-set design.
• Experience with computational reproducibility and containerized environments.
Application Process (Takes 20–30 mins to complete)
• Upload resume
• AI interview based on your resume
• Submit form
Resources & Support
• For details about the interview process and platform information, please check:
• For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas