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Data Science Research Assistant Remote Jobs in Wisconsin

DataAnnotation

Data Science Consultant

Wausau, WI · On-site +1

$60/hr

... research, or any other quantitative field, if you think rigorously about data and models, your ... Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ...

DataAnnotation

Data Science Consultant

Oregon, WI · On-site +1

$40/hr

... research, or any other quantitative field, if you think rigorously about data and models, your ... Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ...

DataAnnotation

Data Science Consultant

Madison, WI · On-site +1

$40/hr

... research, or any other quantitative field, if you think rigorously about data and models, your ... Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ...

DataAnnotation

$40/hr

... research, or any other quantitative field, if you think rigorously about data and models, your ... Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ...

DataAnnotation

$40/hr

... research, or any other quantitative field, if you think rigorously about data and models, your ... Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New ...

DataAnnotation

$40/hr

... remote work and setting your own schedule. We are looking for experienced quantitative ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

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Data Science Research Assistant Remote information

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 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.

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 popular job titles related to Data Science Research Assistant Remote jobs in Wisconsin? For Data Science Research Assistant Remote jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Data Science Research Assistant Remote jobs in Wisconsin look for? The top searched job categories for Data Science Research Assistant Remote jobs in Wisconsin are:
What cities in Wisconsin are hiring for Data Science Research Assistant Remote jobs? Cities in Wisconsin with the most Data Science Research Assistant Remote job openings:
Data Science Research Assistant Remote jobs near you
Data Science Consultant

Data Science Consultant

DataAnnotation

Wausau, WI • On-site, Remote

$60/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr

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