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Data Science Intern - Fall 2026

Atlanta, GA

$30/hr

Success in open-source or competitive projects such as Big Data Bowl, Kaggle, or academic research in sports analytics or forecasting. Our Internship Program at a Glance Our interns will work onsite ...

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DataAnnotation

Psychometrician - AI Trainer

Florida, NY · On-site +1

$60/hr

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 ...

DataAnnotation

Economic Analyst - AI Trainer

Helena, MT · On-site +1

$60/hr

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 ...

DataAnnotation

Psychometrician - AI Trainer

Knoxville, TN · On-site +1

$60/hr

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 ...

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Kaggle information

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$165K

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How much do kaggle jobs pay per year?

As of Jun 7, 2026, the average yearly pay for kaggle in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

How does a Data Scientist working on Kaggle competitions typically collaborate with team members to achieve better results?

Data Scientists participating in Kaggle competitions often work in teams to leverage diverse skill sets and perspectives. Team members share code, discuss problem-solving strategies, and review each other's models to find the most effective approaches. Collaboration usually happens through online communication platforms, version control systems like GitHub, and shared notebooks on Kaggle itself. This teamwork not only enhances solution quality but also provides valuable learning and networking opportunities within the data science community.

What is Kaggle and what do people do on it?

Kaggle is an online platform that hosts data science and machine learning competitions, as well as datasets and educational resources. Users, often called 'Kagglers', participate in challenges by building predictive models using real-world data. Kaggle also offers a collaborative environment where users can share code, discuss problems, and learn from each other. Many data scientists and machine learning enthusiasts use Kaggle to improve their skills, showcase their expertise, and connect with the global data community.

What is the difference between Kaggle vs Data Scientist?

AspectKaggleData Scientist
Required CredentialsNone mandatory; competitive programming skills often preferredTypically requires a degree in data science, statistics, or related fields
Work EnvironmentOnline platform, competitions, and community-based projectsCorporate or research settings, working on real-world data problems
Employer & Industry UsageUsed by individuals for skill development and competitionsEmployed by companies across industries for data analysis and modeling
Common Search & Comparison IntentYesYes

While Kaggle is primarily an online platform for data science competitions and skill development, Data Scientists work within organizations to analyze data and build models for business solutions. Kaggle can be a stepping stone to a Data Scientist role, but they are distinct in their work environment and employment context.

What are the key skills and qualifications needed to thrive as a Data Scientist on Kaggle, and why are they important?

To thrive as a Data Scientist on Kaggle, you need a solid background in statistics, machine learning, data analysis, and proficiency in programming languages such as Python or R. Experience with technical tools like Jupyter Notebooks, data visualization libraries (e.g., Matplotlib, Seaborn), and familiarity with Kaggle's platform and competition formats are essential. Strong problem-solving abilities, creativity, and effective communication of results set top performers apart. These competencies are crucial for developing innovative solutions, sharing insights, and excelling in competitive data science environments.
More about Kaggle jobs
What states have the most Kaggle jobs? States with the most job openings for Kaggle jobs include:
What job categories do people searching Kaggle jobs look for? The top searched job categories for Kaggle jobs are:
Kaggle jobs near you
Infographic showing various Kaggle job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Astrophysicist - AI Trainer

Astrophysicist - AI Trainer

DataAnnotation

Raleigh, NC • On-site, Remote

$60/hr

Full-time

This job post has expired 1 day ago. 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 such as 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. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. 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). #J-18808-Ljbffr

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