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Remote Data Science Unpaid Intern Jobs in Rochester, NY

Bachelor's degree in Computer Science, Information Systems, Business, or equivalent experience. Why ... data, and AI solutions. We combine deep technical expertise with a collaborative culture that ...

Epic Denials Management Operator

Rochester, NY · Remote

$17.75 - $23.75/hr

... operational data For individuals assigned and/or hired to work in a remote role, Deloitte is ... Review AR aging reports and work queues to identify unpaid and delayed claims. Follow up with third ...

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and ...

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... Evaluate scientific accuracy in narrative sections such as efficacy, safety summaries, discussion ...

Remote micro1 is engaging Medical Writers / Clinical Document Authors to participate in a customer ... Evaluate scientific accuracy in narrative sections such as efficacy, safety summaries, discussion ...

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Remote Data Science Unpaid Intern information

See Rochester, NY salary details

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How much do remote data science unpaid intern jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for remote data science unpaid intern in Rochester, NY is $16.81, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $18.99 per hour, depending on experience, location, and employer.
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AI Trainer - Microbiology Expert

micro1 AI

Rochester, NY • Remote

$70 - $90/hr

Part-time

Posted 11 days ago


Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer 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.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.