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Remote Manual Testing Insurance Domain Jobs in Connecticut

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Remote Manual Testing Insurance Domain information

What is the difference between Remote Manual Testing Insurance Domain vs Remote Automation Testing Insurance Domain?

AspectRemote Manual Testing Insurance DomainRemote Automation Testing Insurance Domain
Required SkillsManual testing, insurance domain knowledge, attention to detailAutomation tools, scripting, insurance domain knowledge
Work EnvironmentPrimarily manual testing processes, collaboration with QA teamsDeveloping and maintaining automated test scripts, integration with CI/CD
CertificationsISTQB, insurance-specific certificationsISTQB, automation testing certifications like Selenium, UFT
Industry UsageCommon in initial testing phases, smaller projectsUsed for regression, load testing, larger projects

Remote Manual Testing Insurance Domain focuses on manual test execution within the insurance industry, requiring domain knowledge and attention to detail. Remote Automation Testing Insurance Domain involves developing automated tests, requiring scripting skills and automation tools. Both roles are vital in insurance software testing but differ in approach, tools, and scope.

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Remote Manual Testing Insurance Domain jobs near you

AI Training Specialist - Cheminformatics

micro1 AI

Waterbury, CT • Remote

$80 - $110/hr

Part-time

This job post has expired today. Applications are no longer accepted.

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

Apply