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Data Scientist Intern Jobs in Ridgefield, CT (NOW HIRING)

Group1001

Quantitative Analysis Intern

Stamford, CT · On-site

We are seeking an intern to join our Quantitative Analysis Department for FALL 2026. Primary ... CE Data Science Project To provide CE with more actionable data for making better and more ...

Group1001

Quantitative Analysis Intern

Stamford, CT · Hybrid

We are seeking an intern to join our Quantitative Analysis Department for FALL 2026. Primary ... CE Data Science Project To provide CE with more actionable data for making better and more ...

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All JobsData Scientist Intern JobsData Scientist Intern Jobs in Ridgefield, CT

Data Scientist Intern information

See Ridgefield, CT salary details

$45.8K

$164.3K

$242.5K

How much do data scientist intern jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data scientist intern in Ridgefield, CT is $164,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,000.00 and $169,300.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Scientist Intern, you generally need a strong foundation in statistics, programming (often Python or R), and data analysis, often supported by coursework in computer science or related fields. Familiarity with tools such as Jupyter Notebook, SQL, and machine learning libraries like scikit-learn or TensorFlow is typically expected. Strong problem-solving skills, curiosity, and effective communication set standout candidates apart in this role. These skills and qualities are crucial for extracting insights from data, collaborating with diverse teams, and contributing meaningful solutions to real-world problems.

What types of projects and tasks can I expect to work on as a data scientist intern?

As a Data Scientist Intern, you can expect to work on a variety of data-driven projects such as cleaning and analyzing datasets, building predictive models, and generating data visualizations to support business decisions. You'll often collaborate with other data scientists, engineers, and business teams to tackle real-world problems and may be asked to present your findings to stakeholders. These experiences are designed to help you develop technical skills, gain exposure to industry tools and methodologies, and understand how data science contributes to organizational goals.

What is a data scientist intern?

Data Scientist Interns are individuals, often students or recent graduates, who work temporarily in organizations to gain practical experience in data science. Their main responsibilities include collecting, cleaning, analyzing, and visualizing data under the guidance of experienced data scientists. Interns may also assist in building machine learning models, generating reports, and presenting insights to help solve real business problems. The internship provides valuable hands-on experience and helps interns develop technical and analytical skills necessary for a full-time data science role.

What is the difference between Data Scientist Intern vs Data Analyst Intern?

AspectData Scientist InternData Analyst Intern
Required CredentialsTypically pursuing or holding a degree in Data Science, Computer Science, or related fieldsUsually pursuing or holding a degree in Statistics, Mathematics, or related fields
Work EnvironmentInvolves building predictive models, machine learning, and advanced analyticsFocuses on data cleaning, reporting, and descriptive analytics
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprises for complex data projectsCommon in retail, marketing, and business intelligence roles across industries

While both roles involve working with data, a Data Scientist Intern typically engages in advanced analytics and machine learning projects, whereas a Data Analyst Intern focuses on data reporting and descriptive analysis. The roles differ mainly in complexity and technical skills required, but both serve as entry points into data-driven careers.

What are the most commonly searched types of Data Scientist jobs in Ridgefield, CT? The most popular types of Data Scientist jobs in Ridgefield, CT are:
What cities near Ridgefield, CT are hiring for Data Scientist Intern jobs? Cities near Ridgefield, CT with the most Data Scientist Intern job openings:
Data Scientist Intern jobs near you
Infographic showing various Data Scientist Intern job openings in Ridgefield, CT as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $164,349 per year, or $79 per hour.

Data Engineering Internship (Summer 2027)

Castleton Commodities International LLC

Stamford, CT

$122K - $146K/yr

Full-time

Posted 18 days ago

Job description

Application Deadline: September 1, 11:59 pm EST

Program Summary - Data Science & Technology Internship

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 Data Engineering Interns to join our Global Data Science & Technology team in Houston, TX, Stamford, CT, & New York City offices. The Data Engineering Intern will work closely with our Data Science, Data Engineering and Commercial teams to build and optimize data pipelines that power our analytics, forecasting, and investment decision-making processes. This is a hands-on technical internship ideal for someone who enjoys solving real-world data challenges, especially around ingesting, scraping, and managing large datasets across the commodity markets.

Responsibilities:

  • Develop and maintain robust data ingestion pipelines from various internal and external sources, including APIs, FTP endpoints, and cloud data providers.
  • Develop data ingestion and transformation pipelines using Python and SQL, publishing Snowflake for downstream use in analytics and forecasting tools.
  • Work on data architecture and data management projects for both new and existing data sources.
  • Design and implement ETL processes to clean, normalize, and store structured and semi-structured data in Snowflake, our core relational data warehouse.
  • Analyze data pipeline performance and implement optimizations to improve efficiency and reliability.
  • Conduct data quality checks and build validation logic to identify anomalies and ensure data integrity for use by commercial trading and analytics teams.
  • Automate data workflows using Python, SQL, and orchestration tools (e.g., Airflow or similar).
  • Assist in transitioning legacy datasets and codebases into scalable, cloud-native workflows aligned with our modern data architecture.
  • Document data sources, pipeline logic, and data models to ensure maintainability and knowledge transfer.

Qualifications:

  • Currently pursuing a Bachelor's or higher degree in Computer Science, Engineering, Management Information Systems, or related technical field.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Strong programming experience in Python (preferred libraries: pandas, NumPy, SQL alchemy, etc.).
  • Strong understanding of SQL and experience querying relational databases (Snowflake a plus).
  • Exposure to or interest in cloud platforms (e.g., AWS, Azure), particularly with cloud data storage and compute.
  • Familiarity with web scraping frameworks and handling large-scale structured and unstructured data sources.

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