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Amazon Data Science Internship Jobs in Connecticut

Guardianlife

Data Scientist, Agentic AI

Stamford, CT · Hybrid

$95K - $156K/yr

Guardian created theData Science Lab (DSL)to reimagine insurance in light of emerging technology ... Interns are not eligible for most Company benefits. Equal Employment Opportunity Guardian is an ...

Synchrony

BLP Intern - Data Analytics

Stamford, CT

Business Leadership Program Internship Overview: Synchrony's Business Leadership Program Summer ... leveraging data science to develop cutting-edge machine learning models to predict customer ...

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Amazon Data Science Internship information

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How much do amazon data science internship jobs pay per hour?

As of Jul 31, 2026, the average hourly pay for amazon data science internship in Connecticut is $21.41, according to ZipRecruiter salary data. Most workers in this role earn between $16.44 and $23.32 per hour, depending on experience, location, and employer.

How much does Amazon pay to interns?

Amazon Data Science Interns typically receive a competitive hourly wage, which can range from $20 to $40 per hour depending on location and experience. Internships usually last 12 to 16 weeks and may include benefits such as housing stipends or transportation allowances in some locations.

What are the key skills and qualifications needed to thrive as an Amazon Data Science Intern, and why are they important?

To thrive as an Amazon Data Science Intern, you need a solid background in statistics, programming (such as Python or R), and data analysis, often supported by progress toward a degree in computer science, mathematics, or a related field. Familiarity with tools like SQL, AWS, machine learning libraries (e.g., scikit-learn, TensorFlow), and version control systems is highly valued. Strong problem-solving skills, curiosity, and effective communication help interns collaborate and present findings to both technical and non-technical stakeholders. These abilities are crucial for delivering actionable insights and contributing to impactful projects in Amazon's fast-paced, data-driven environment.

What is an Amazon Data Science Internship?

An Amazon Data Science Internship is a temporary position for students or recent graduates to work with Amazon’s data science teams. Interns apply statistical analysis, machine learning, and data engineering skills to solve real-world business problems. The internship provides hands-on experience with large datasets and exposure to Amazon’s tools, technologies, and culture. Interns also have opportunities to collaborate with experienced data scientists and contribute to impactful projects. This experience can help launch a career in data science, especially in the tech industry.

Does Amazon have data science internships?

Yes, Amazon offers data science internships for students and recent graduates, typically lasting 12 weeks during the summer. These internships provide hands-on experience with large-scale data analysis, machine learning, and cloud tools like AWS, and often require strong programming skills in Python or R.

What types of projects do interns typically work on during an Amazon Data Science Internship?

As an Amazon Data Science intern, you can expect to work on real-world projects that directly impact business decisions. Common projects include developing predictive models, performing exploratory data analysis, and collaborating with software engineers to implement machine learning solutions. Interns often partner with cross-functional teams, such as product managers and business analysts, to translate data insights into actionable recommendations. This hands-on experience helps interns build technical and communication skills while gaining exposure to Amazon's fast-paced, data-driven environment.

How much do Amazon data science interns make?

Amazon data science interns typically earn between $30 and $40 per hour, depending on experience and location. Interns often work full-time during the summer and may receive additional benefits such as stipends or housing support.

Is it hard to get an internship at Amazon?

Securing an Amazon Data Science Internship is competitive due to high applicant volume and rigorous selection processes. Candidates typically need strong academic backgrounds, relevant technical skills such as machine learning and data analysis, and demonstrated problem-solving abilities. The application process often includes multiple interviews and technical assessments.
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Amazon Data Science Internship jobs near you
Infographic showing various Amazon Data Science Internship job openings in Connecticut as of July 2026, with employment types broken down into 1% Locum Tenens, 95% Full Time, 2% Part Time, and 2% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $44,529 per year, or $21.4 per hour.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

Full-time

Posted 10 days ago

Job description

Application Deadline: September 1, 11:59pm EST
Program Summary - Commercial Technology Internships
Company Overview:
Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.
Position Overview:
CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.
Responsibilities:
  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:
  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

Apply