Computational Research Scientist

Job not on LinkedIn

🕒 July 27

🗽 New York – Remote

🗽 New York – Remote

💵 $55 - $85 / hour

⏰ Full Time

🟢 Junior

🧬 Research Scientist

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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24-MAG

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤝 B2B

💼 Consulting

B2B • Consulting

24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.

📋 Description

• Research Task Design: Transform real research workflows into challenging, multi-step benchmark tasks • Technical Implementation: Implement complete reference solutions using Python and notebook environments • Evaluation Criteria & Reference Solutions: Define what distinguishes rigorous research reasoning from plausible but unsupported analysis • Model Output Review: Evaluate AI-generated attempts across computational research tasks • Research Collaboration: Work closely with researchers, task authors, and fellow subject-matter experts

🎯 Requirements

• At least 1 year of experience in an active academic, industry, government, or national-laboratory research role • An MSc or PhD in a STEM field, computational social science, computational humanities, or another research-intensive discipline • Significant experience using Python for analysis, simulation, modelling, or data pipelines • Strong grounding in experimental design, hypothesis testing, and rigorous evaluation • Experience interpreting complex datasets and producing evidence-based conclusions • Working familiarity with Git, IDEs, and Jupyter or Colab notebooks • Strong written communication and technical documentation skills • Ability to work independently through ambiguous and open-ended research problems • Reliable availability for approximately 35 hours per week.