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Internship Data Science Trading Jobs in Connecticut

Associate Data Scientist

Stamford, CT · Hybrid

$62K - $63K/yr

Knowledge of computer science principles such as algorithms, data structures and design methodologies Preferred Qualifications Experience * Internship experience in a data scientist role #LI-JV1 ...

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 ...

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 ...

Collaborate with the Information Technology team and data scientists to ensure data quality, integrity, and consistency. Job Requirements Experience: Internship and/or academic experience involving ...

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses ... Communicate system design, trade-offs, and limitations clearly to technical and non-technical ...

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Internship Data Science Trading information

What is the difference between Internship Data Science Trading vs Data Analyst?

AspectInternship Data Science TradingData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in data-related field, analytical skills, proficiency in data tools
Work EnvironmentFinancial firms, trading floors, collaborative teamsVarious industries, offices, cross-functional teams
Employer & Industry UsageFinance, trading firms, investment banksMultiple sectors including finance, marketing, healthcare

Internship Data Science Trading focuses on applying data science skills to trading strategies within financial firms, often involving real-time data analysis. Data Analysts work across industries analyzing data to inform business decisions. While both roles require analytical skills and familiarity with data tools, internships are more training-oriented, whereas Data Analysts are more experienced roles in data interpretation and reporting.

What are the most commonly searched types of Data Science Trading jobs in Connecticut?

The most popular types of Data Science Trading jobs in Connecticut are:

What cities in Connecticut are hiring for Internship Data Science Trading jobs?

Cities in Connecticut with the most Internship Data Science Trading job openings:

Infographic showing various Internship Data Science Trading job openings in Connecticut as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 11% Part Time, 2% Temporary, and 5% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

Full-time

Posted 29 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.