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Data Science Research Assistant Remote Jobs in Raleigh, NC

** Please note that the selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable

hackajob is collaborating with LexisNexis to connect them with exceptional professionals for this role. ** Please note that the selected individual for this role will be expected to work in our

Principal Data Scientist

Raleigh, NC ยท On-site +1

$147K - $243K/yr

*Telecommuting role to be performed anywhere in the U.S. Build data science solutions for business challenges including customer propensity, product forecasting, and recommender systems. Use machine

Principal Data Scientist

Raleigh, NC ยท On-site +1

$147K - $243K/yr

*Telecommuting role to be performed anywhere in the U.S. Build data science solutions for business challenges including customer propensity, product forecasting, and recommender systems. Use machine

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Data Science Research Assistant Remote information

See Raleigh, NC salary details

$8

$21

$30

How much do data science research assistant remote jobs pay per hour?

As of Jul 23, 2026, the average hourly pay for data science research assistant remote in Raleigh, NC is $21.30, according to ZipRecruiter salary data. Most workers in this role earn between $17.98 and $24.76 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Research Assistant (Remote), and why are they important?

To thrive as a Data Science Research Assistant (Remote), a solid background in statistics, programming (Python or R), and data analysis, often supported by relevant coursework or a degree, is essential. Familiarity with data visualization tools (e.g., Tableau), databases (SQL), and platforms like Jupyter Notebook, as well as experience with machine learning libraries, is typically required. Strong problem-solving abilities, attention to detail, self-motivation, and effective remote communication skills make candidates stand out. These competencies are crucial for managing complex data tasks, collaborating with team members virtually, and delivering reliable analytical insights.

What are common challenges faced by remote Data Science Research Assistants, and how can they be addressed?

Remote Data Science Research Assistants often encounter challenges such as maintaining clear communication with team members, managing time across different projects, and accessing necessary datasets or computing resources. Overcoming these hurdles typically involves leveraging collaboration tools like Slack or Zoom for regular check-ins, setting clear expectations with supervisors on deliverables, and ensuring secure, remote access to data and software. Proactively seeking feedback and participating in virtual team meetings can help foster a sense of connection and keep projects on track.

What is the difference between Data Science Research Assistant Remote vs Data Analyst Remote?

AspectData Science Research Assistant RemoteData Analyst Remote
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's or Master's in Data Analysis, Statistics, or related field
Work EnvironmentRemote research projects, academic or research institutionsRemote data interpretation and reporting for various industries
Employer & Industry UsageUniversities, research labs, tech companiesBusiness, finance, healthcare, marketing

While both roles involve working with data remotely, Data Science Research Assistants focus on research projects, often in academic or research settings, requiring a strong foundation in data science and statistics. Data Analysts typically analyze and interpret data for business insights across various industries. The roles share similar credentials but differ in their primary focus and work environment.

What are Data Science Research Assistants (Remote)?

A Data Science Research Assistant (Remote) is a professional who supports data scientists and research teams by collecting, cleaning, analyzing, and visualizing data, often from a remote location. Their responsibilities may include assisting with experiment design, performing statistical analyses, preparing datasets, creating reports, and helping to develop or test machine learning models. Working remotely, they utilize collaboration tools and cloud platforms to work efficiently with distributed teams. This role is ideal for individuals with strong analytical skills, programming knowledge (such as Python or R), and an interest in research and data-driven problem solving.
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