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Google Internship Data Science Jobs in Connecticut

Customer Operations

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 null ...

Gartner

Data Analyst - 2026/2027 graduates

Stamford, CT · On-site

  • Retirement

  • PTO

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 ...

Gartner

Data Analyst - 2026/2027 graduates

Stamford, CT

  • Retirement

  • PTO

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 ...

Gartner

Data Analyst - 2026/2027 graduates

Stamford, CT · On-site

  • Retirement

  • PTO

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 ...

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Google Internship Data Science information

What is a Google internship in data science?

A Google Internship in Data Science is a temporary, paid position where students or recent graduates work with Google's data science teams. Interns are involved in analyzing large datasets, building machine learning models, and providing insights to improve Google products and services. The internship offers hands-on experience, mentorship, and exposure to real-world data science challenges in a leading tech company. Applicants typically need strong analytical skills, proficiency in programming languages like Python or R, and a background in statistics or computer science.

What types of projects does a data science intern typically work on during a Google internship?

Data Science interns at Google often collaborate on high-impact projects alongside full-time data scientists and engineers. Projects may include analyzing large datasets to identify trends, building machine learning models, or developing data-driven solutions for products and services. Interns are encouraged to contribute ideas, participate in code reviews, and present findings to their teams. This hands-on experience allows interns to gain exposure to Google's tools and methodologies, while also building a strong foundation for future roles in data science.

What are the key skills and qualifications needed to thrive as a Google data science intern, and why are they important?

To thrive as a Google Data Science Intern, you need a solid background in statistics, programming (such as Python or R), and data analysis, typically supported by current enrollment in a relevant degree program. Familiarity with tools like SQL, TensorFlow, and data visualization platforms is commonly expected, along with experience in machine learning frameworks. Strong problem-solving abilities, effective communication, and collaboration skills help interns contribute meaningfully to cross-functional teams. These skills are essential to analyze complex datasets, deliver actionable insights, and succeed in Google's fast-paced, innovative environment.

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

AspectGoogle Internship Data ScienceGoogle Data Analyst Internship
Required SkillsProgramming (Python, R), statistics, machine learning, data modelingData analysis, SQL, Excel, visualization tools
Work EnvironmentCollaborative, research-focused, technical projectsBusiness-oriented, reporting, data interpretation
Industry UsageResearch, product development, machine learning modelsBusiness insights, performance metrics, reporting

Google Internship Data Science roles focus on developing machine learning models and advanced analytics, requiring programming and statistical skills. In contrast, Google Data Analyst Internships emphasize data interpretation, reporting, and visualization for business decisions. Both roles are valuable within Google's data ecosystem but serve different functions based on technical depth and business application.

What are popular job titles related to Google Internship Data Science jobs in Connecticut?

For Google Internship Data Science jobs in Connecticut, the most frequently searched job titles are:

What job categories do people searching Google Internship Data Science jobs in Connecticut look for?

The top searched job categories for Google Internship Data Science jobs in Connecticut are:

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

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

Google Internship Data Science jobs near you
Infographic showing various Google Internship Data Science job openings in Connecticut as of June 2026, with employment types broken down into 3% As Needed, 84% Full Time, 8% Part Time, and 5% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

Full-time

Re-posted 1 hour 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