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Open nowFirst seen 3 hours ago

Remote | Life Sciences Research Expert (Python) — $60–$120/hour

24-MAG260 open roles

Where
New York, United States, Remote
Work mode
Remote
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Your applicationOpen nowRemote | Life Sciences Research Expert (Python) — $60–$120/hour24-MAG · New York, United States, Remote

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The clock on this job

Early applications get read.

11.9% of postings close within 7 days. Measured by our own scanner across the market. 24-MAG postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.9%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 3 hours ago

24-MAG median: 1 days open

The posting

We are sharing a specialised remote consulting opportunity for experienced Life Sciences Researchers with strong Python programming skills and expertise in biology, biomedical science, computational research, neuroscience, or related scientific disciplines to contribute to advanced AI training and evaluation initiatives.

Selected professionals will develop, solve, and evaluate challenging scientific research problems, conduct reproducible computational analyses, and assess AI-generated scientific solutions for technical accuracy and methodological rigour. The work combines scientific domain expertise with Python-based data analysis, computational modelling, code validation, and structured research evaluation to help improve the reasoning, accuracy, and reliability of advanced AI systems.

Key Responsibilities

Life Sciences Research & Scientific Problem Development

  • Develop technically rigorous scientific problems reflecting real-world challenges in biology, medicine, and related research disciplines
  • Apply specialised scientific knowledge to create challenging research questions requiring analytical reasoning and domain expertise
  • Design realistic scientific scenarios involving biological systems, experimental data, and computational research methods
  • Evaluate complex scientific concepts, assumptions, and methodologies to ensure technical accuracy
  • Contribute to the development of structured scientific tasks suitable for advanced AI training and evaluation

Python-Based Scientific Computing & Data Analysis

  • Develop reproducible Python-based analyses, computational models, simulations, and data-processing workflows
  • Analyse scientific datasets using appropriate statistical, numerical, and computational techniques
  • Apply Python libraries such as NumPy, pandas, SciPy, Matplotlib, and scikit-learn to research-oriented problems
  • Build clear, well-documented computational solutions that demonstrate sound scientific reasoning
  • Evaluate the accuracy, efficiency, and reproducibility of scientific code and analytical workflows

Biological Modelling & Interdisciplinary Research

  • Apply scientific expertise across relevant disciplines, including computational biology, neuroscience, genetics, and biomedical research
  • Develop analytical approaches to problems involving molecular biology, biotechnology, genomics, or biological data science
  • Interpret experimental findings, biological datasets, and computational results within appropriate scientific frameworks
  • Assess the suitability of modelling techniques, statistical assumptions, and research methodologies
  • Support interdisciplinary scientific evaluation tasks requiring quantitative reasoning and computational problem-solving

AI Training & Scientific Solution Evaluation

  • Review and validate AI-generated scientific analyses, computational solutions, and Python code
  • Identify errors in technical reasoning, scientific assumptions, mathematical calculations, and programming logic
  • Evaluate scientific responses for correctness, clarity, completeness, and methodological consistency
  • Develop structured feedback explaining inaccuracies, alternative approaches, and opportunities for improvement
  • Contribute expert-level assessments to strengthen AI performance across complex scientific and computational tasks

Research Quality Assurance & Technical Documentation

  • Review scientific solutions and computational workflows for reproducibility, accuracy, and technical completeness
  • Produce clear explanations of analytical methods, assumptions, results, and scientific conclusions
  • Document Python implementations and research findings in a structured, accessible format
  • Apply rigorous quality standards to scientific problem-solving, code review, and research evaluation
  • Provide constructive technical feedback supporting continuous improvement of AI-generated scientific content

Ideal Profile

  • PhD, MD, or master's degree with substantial research experience in a relevant life sciences discipline
  • Strong background in scientific or applied research demonstrated through publications, thesis work, computational projects, industry research, or equivalent accomplishments
  • Practical Python programming experience for scientific computing, data analysis, modelling, or simulation
  • Expertise in one or more areas including medicine, biomedical science, computational biology, neuroscience, or molecular and cellular biology
  • Experience in biotechnology, bioinformatics, genetics, genomics, ecology, evolutionary biology, or biostatistics is highly relevant
  • Familiarity with scientific computing libraries such as NumPy, pandas, SciPy, Matplotlib, scikit-learn, or domain-specific research tools
  • Experience working with Jupyter notebooks, reproducible computational workflows, and scientific datasets
  • Strong understanding of research methodologies, statistical reasoning, and computational problem-solving
  • Ability to develop technically challenging scientific questions and produce accurate, well-supported solutions
  • Demonstrated ability to review scientific code, validate computational results, and identify reasoning or implementation errors
  • Excellent analytical, critical-thinking, and problem-solving capabilities
  • Strong written communication skills, including the ability to explain sophisticated scientific concepts and computational methods clearly
  • Exceptional attention to detail and commitment to scientific accuracy, reproducibility, and research quality
  • Ability to work independently, manage assigned research tasks, and meet established technical standards
  • Familiarity with AI evaluation, machine learning, or interdisciplinary computational research is advantageous

Engagement Details

  • Freelance / contract engagement
  • Fully remote — open worldwide
  • Compensation: $60–$120/hour advertised rate range
  • Payment Structure: Output-based compensation, with payment made per completed task that meets project specifications
  • Expected Commitment: Approximately 15 hours per week
  • Flexible Schedule: Professionals may select their preferred working hours and days, including weekends
  • 100 available openings
  • Specialised scientific consulting role spanning life sciences research, Python programming, computational analysis, and AI evaluation
  • Work will involve scientific problem development, Python-based modelling, code validation, research analysis, and AI-generated solution assessment
  • Task completion requirements and compensation will depend on the specifications of individual assignments
  • Selection may include screening questions, an approximately 30-minute AI interview, and a hiring manager review
  • Selected professionals should be prepared to begin initial assignments within 24–48 hours of completing onboarding

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

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