Data Scientist, Quantitative Analyst

Job not on LinkedIn

🕒 6 days ago

🗽 New York – Remote

🗽 New York – Remote

💵 $55 - $85 / hour

⏰ Full Time

🟢 Junior

📉 Data Analyst

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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

• Create realistic analytical tasks based on professional data science and quantitative research workflows • Develop assignments involving messy data, anomaly detection, correlation analysis, hypothesis testing, and method comparison • Design complex, multi-step problems requiring statistical judgment and careful interpretation • Ensure tasks include realistic constraints, datasets, assumptions, and decision-making objectives • Complete reference analyses using Jupyter Notebook or Google Colab • Build clear and reproducible workflows using Python, pandas, NumPy, and related libraries • Document data-cleaning decisions, calculations, statistical methods, and analytical conclusions • Validate intermediate results, spot checks, visualisations, and final recommendations • Design fair comparisons between analytical models, algorithms, or statistical approaches • Evaluate performance using appropriate metrics, manual checks, and sensitivity analyses • Identify methodological trade-offs, limitations, and sources of uncertainty • Produce recommendations supported by transparent quantitative evidence • Review model-generated analyses for statistical accuracy, methodological rigour, and sound interpretation • Verify whether calculations, correlations, hypotheses, and conclusions are supported by the data • Identify coding errors, unsupported assumptions, misleading summaries, and analytical shortcuts • Explain where and why model outputs fail to meet professional data-analysis standards • Work closely with researchers, task authors, and fellow quantitative specialists • Compare evaluation decisions to maintain consistent benchmark standards • Refine tasks, reference notebooks, and grading criteria based on testing outcomes • Document recurring model weaknesses and opportunities for stronger evaluation coverage

🎯 Requirements

• At least 1 year of experience in data science, quantitative analysis, research engineering, or another research-intensive analytical role • Deep hands-on experience with data cleaning, statistical correlation, hypothesis testing, and interpretation • Strong proficiency in Python, including pandas, NumPy, or comparable analytical libraries • Experience using Jupyter Notebook or Google Colab for analysis and reporting • Working familiarity with Git and reproducible analytical workflows • Ability to communicate complex quantitative findings clearly to technical and non-technical decision-makers • Strong attention to detail and confidence working through ambiguous, open-ended problems • Reliable availability for approximately 35 hours per week • A master's degree or PhD in statistics, data science, mathematics, economics, computer science, engineering, or another quantitative discipline is highly relevant. • Equivalent practical experience in a research-heavy analytical field may also be considered. • Academic or professional research involving statistical modelling, experimentation, or large-scale data analysis may strengthen an application. • Publications, technical reports, open-source work, or impactful analytical projects may also be valuable.