Remote | Experienced & Credentialed Data Scientists -- $120-$180/hour
Job Description
Job Description
We are sharing a specialised part-time consulting opportunity for highly credentialed data scientists with strong academic backgrounds and significant industry experience across quantitative, scientific, and computational fields.
This role supports current and upcoming remote consulting opportunities focused on structured technical workflows, advanced data science work, technical evaluation, and high-quality project execution. Selected professionals will apply their data science expertise to contribute high-level analytical reasoning, support complex technical workflows, follow technical instructions with precision, and contribute to high-quality technical deliverables. This opportunity is especially well-suited to professionals with rigorous academic training and real-world experience in data-intensive, research-driven, and computationally complex environments.
Key Responsibilities
Professionals in this role may contribute to:
Advanced Data Science & Analytical Work
- Apply strong data science expertise across quantitative, scientific, or computational problem domains
- Contribute technical judgment informed by advanced academic training and real-world industry experience
- Support high-quality analytical work in research-driven or production-oriented environments
Machine Learning & Data Workflow Support
- Work with cloud-based data and machine learning tools to support technical workflows
- Apply experience with modern data environments used for large-scale analysis, modeling, or experimentation
- Contribute to structured, high-level work requiring both analytical depth and practical execution skills
Cross-Domain Technical Contribution
- Bring domain expertise from fields such as quant trading, bioinformatics, astrophysics, applied computational mathematics, or related areas
- Support technically demanding projects requiring strong reasoning, modeling, and data interpretation capabilities
- Help maintain high standards of quality, rigor, and precision across project work
Ideal Profile
Strong candidates may have:
- PhD or MS in a related quantitative, scientific, or computational field
- Significant industry work experience in data science or adjacent technical functions
- Background in fields such as quant trading, bioinformatics, astrophysics, applied computational mathematics, or similar domains
- Strong analytical, quantitative, and problem-solving skills
- Ability to apply rigorous technical reasoning in complex real-world environments
- Strong attention to detail and comfort working in advanced technical settings
Preferred Qualifications
- Experience with cloud-based data and machine learning tools such as Google Colab, BigQuery, Databricks, Snowflake, or AWS and Azure analytics tools
- Experience working across large-scale data pipelines, modeling workflows, or research-oriented ML environments
- Ability to contribute in technically demanding and interdisciplinary problem spaces
- Strong communication skills for explaining complex technical reasoning clearly
Why This Opportunity
- Apply advanced data science expertise to high-impact technical work
- Contribute in rigorous, research-driven, and computationally sophisticated environments
- Work remotely with flexible scheduling and competitive compensation
- Bring deep quantitative and scientific experience to technically demanding projects
Contract Details
- Independent contractor role
- Fully remote with flexible scheduling
- Compensation range of $120–$180 per hour
- Weekly payments via Stripe or Wise
- Projects may be extended, shortened, or concluded early depending on project needs and performance
- Work will not involve access to confidential or proprietary information from any employer, client, or institution
- Please note: We are unable to support H1-B or STEM OPT candidates at this time
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.
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