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Summer Data Science Jobs in Connecticut (NOW HIRING)

Synchrony

BLP Intern - Data Analytics

Stamford, CT

During the summer, each BLP Intern is provided with project work that is important to our business ... leveraging data science to develop cutting-edge machine learning models to predict customer ...

AQR

2027 Trading Summer Analyst

Greenwich, CT · On-site

The Internship Program Our 10-week summer program puts real work of the firm in your hands. You ... They enjoy testing hypotheses and using data science to solve real-world trading and investment ...

AQR

2027 Trading Summer Analyst

Greenwich, CT

The Internship Program Our 10-week summer program puts real work of the firm in your hands. You ... They enjoy testing hypotheses and using data science to solve real-world trading and investment ...

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Summer Data Science information

What is the difference between Summer Data Science vs Summer Data Analyst?

AspectSummer Data ScienceSummer Data Analyst
Required CredentialsTypically requires coursework or degree in data science, statistics, or related fieldsOften requires degree or coursework in data analysis, statistics, or business analytics
Work EnvironmentCollaborates with data scientists, engineers, and product teams on complex data projectsWorks with business teams to interpret data, generate reports, and support decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for advanced data modelingCommon in marketing, retail, finance, and operations for data reporting and insights

Summer Data Science roles focus on developing predictive models and advanced analytics, often requiring stronger technical skills. Summer Data Analysts typically handle data reporting and visualization to support business decisions. Both roles are valuable in data-driven industries but differ in technical depth and project scope.

What are the key skills and qualifications needed to thrive as a Summer Data Science intern?

To excel as a Summer Data Science Intern, you need a solid understanding of statistics, data analysis, and programming languages like Python or R, often supported by coursework or a degree in a quantitative field. Familiarity with tools such as SQL, Jupyter Notebooks, and data visualization platforms, as well as experience with machine learning libraries, is typically expected. Strong problem-solving abilities, curiosity, and effective communication help interns collaborate and present insights clearly. These skills enable interns to contribute meaningful analyses, adapt quickly to new challenges, and add value to data-driven projects in a short timeframe.

What is a Summer Data Science internship?

A Summer Data Science internship is a temporary, often 8-12 week, position for students or recent graduates to gain hands-on experience in data science during the summer months. Interns typically work on real-world projects involving data collection, cleaning, analysis, and visualization, using tools like Python, R, and SQL. These internships provide valuable exposure to industry practices, mentorship from experienced data scientists, and opportunities to develop technical and analytical skills. They are commonly offered by tech companies, finance firms, healthcare organizations, and startups.

What types of projects can I expect to work on as a Summer Data Science intern?

As a Summer Data Science intern, you can typically expect to work on real-world projects involving data cleaning, exploratory data analysis, and building predictive models under the supervision of experienced data scientists. You may be tasked with analyzing large datasets, visualizing findings, and contributing to presentations that inform business decisions. Collaboration is common, so you'll likely work closely with team members from engineering, analytics, and business units to refine project goals and deliver actionable insights. This hands-on experience is designed to help you develop technical skills while understanding how data science impacts organizational objectives.
What are the most commonly searched types of Data Science jobs in Connecticut? The most popular types of Data Science jobs in Connecticut are:
What are popular job titles related to Summer Data Science jobs in Connecticut? For Summer Data Science jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Summer Data Science jobs in Connecticut look for? The top searched job categories for Summer Data Science jobs in Connecticut are:
What cities in Connecticut are hiring for Summer Data Science jobs? Cities in Connecticut with the most Summer Data Science job openings:
Summer Data Science jobs near you
Infographic showing various Summer Data Science job openings in Connecticut as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

Full-time

Posted 22 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.

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