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Quantitative Research Assistant Jobs (NOW HIRING)

WestEd

Quantitative Research Associate

San Francisco, CA · On-site +1

... assist with participant recruitment and incentive management. * Data Collection - establish and ... Strong knowledge of research and evaluation design and methodology, measurement, and quantitative ...

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How much do quantitative research assistant jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for quantitative research assistant in the United States is $21.91, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $25.48 per hour, depending on experience, location, and employer.

What are quantitative research assistants?

Quantitative research assistants are professionals who support research projects by collecting, analyzing, and interpreting numerical data. They often use statistical software to manage datasets, perform statistical analysis, and help prepare reports or presentations based on their findings. These assistants typically work in academic, scientific, or business settings and collaborate closely with lead researchers or data scientists. Their work helps ensure that research conclusions are based on rigorous and accurate quantitative analysis.

What is the difference between Quantitative Research Assistant vs Data Analyst?

AspectQuantitative Research AssistantData Analyst
Required CredentialsBachelor's degree in statistics, economics, or related fieldBachelor's or master's in data science, statistics, or related field
Work EnvironmentResearch institutions, universities, market research firmsCorporate, finance, healthcare, or tech companies
Employer & Industry UsageAcademic and research settings, market research firmsBusiness analytics, finance, marketing departments
Common Search & ComparisonOften compared for data handling and research tasksCompared for data processing and reporting roles

The main difference is that Quantitative Research Assistants focus on supporting research projects with data collection and analysis in academic or research settings, while Data Analysts typically work in business environments analyzing data to inform decisions. Both roles require strong quantitative skills and similar educational backgrounds, but their work environments and primary objectives differ.

What are the key skills and qualifications needed to thrive as a Quantitative Research Assistant, and why are they important?

To thrive as a Quantitative Research Assistant, you need strong analytical skills, proficiency in statistical methods, and a relevant degree in fields like mathematics, statistics, or economics. Familiarity with statistical software such as R, Stata, SPSS, or Python, as well as experience with data management systems, is typically required. Attention to detail, problem-solving abilities, and effective communication are key soft skills that set candidates apart. These skills are essential for ensuring the accuracy, reliability, and clarity of research findings, which directly impact the quality and credibility of quantitative research projects.

What are some common challenges Quantitative Research Assistants face when managing large datasets, and how can these be addressed?

Quantitative Research Assistants often work with large, complex datasets that can present challenges such as data cleaning, ensuring accuracy, and maintaining data integrity. Handling missing values, outliers, or inconsistent formats requires attention to detail and strong technical skills in statistical software like R, Python, or SPSS. Collaborating closely with research teams can help clarify data requirements and resolve ambiguities early on. Regularly documenting procedures and validating data at each stage helps minimize errors and ensures reliable analysis results.
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Quantitative Research Assistant jobs near you

Quantitative Research Engineer

NUMEUS GROUP

Manhattan, NY • On-site

Full-time

Posted 7 days ago

Job description

Job Summary:
NUMEUS GROUP is seeking an experienced Quantitative Research Engineer to work on their data and research platforms. The role involves developing innovative tools and methodologies to enhance research productivity and improve data analysis capabilities in collaboration with quantitative researchers.
Responsibilities:
• Collaborate with quantitative researchers to understand their workflow, challenges, and requirements, and provide technical solutions to improve their research productivity
• Design, develop, and maintain software tools, platforms, and frameworks that enhance the efficiency and effectiveness of research activities, including data gathering, preprocessing, analysis, and model development
• Identify and implement advanced data processing techniques, algorithms, and statistical methods to optimize research workflows and enhance data analysis capabilities
• Leverage your expertise in software engineering, data engineering, and machine learning to build scalable and robust systems that facilitate large-scale data analysis and experimentation
• Conduct code reviews, provide technical guidance, and mentor junior research engineers to ensure code quality, maintainability, and adherence to best practices
• Collaborate with cross-functional teams, including quantitative researchers, data scientists, and engineering professionals, to integrate research tools and systems into the existing infrastructure
• Assist in the evaluation and implementation of third-party tools, libraries, and data sources that can enhance the research process
• Participate in research discussions, contribute ideas, and provide technical expertise to improve research methodologies and strategies
• Contribute to the development and maintenance of documentation, user guides, and training materials related to research tools and processes
Qualifications:
Required:
• 4+ years experience working in close partnership with quantitative researchers to develop, deploy and maintain quantitatively-driven alpha strategies.
• Masters or Ph.D. in Computer Science, Engineering, Data Science, or a related field
• Exceptional Python programming skills, with a focus on building scalable and efficient systems
• Experience with graph (DAG) representation, analysis, and processing using tools like NetworkX
• Experience with open source distributed computing tools in Python, such as Dask or Ray
• Proficiency in data processing, analysis, and visualization leveraging best-in-class open source tools, libraries, and frameworks (e.g., Pandas, Plotly, SciPy)
• Solid understanding of statistical modeling, machine learning techniques, and their practical applications in quantitative research
• Solid understanding of the differences between L1, L2 and L3 market tick data
• Experience with AWS, Linux and Docker
• Excellent problem-solving skills and the ability to design practical solutions to complex research challenges
• Strong communication and collaboration skills to effectively work with cross-functional teams and translate research requirements into technical solutions
• Ability to travel periodically between our offices in London, NYC, and Zug, Switzerland
Preferred:
• Previous experience at a quantitative hedge fund is strongly preferred.
• Experience in recruiting, mentoring, and guiding junior team members is preferred.
Company:
Numeus is a diversified digital asset manager built to the highest institutional standards. Founded in 2021, the company is headquartered in Zug, CHE, with a team of 51-200 employees. The company is currently Growth Stage.

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