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Internship Bank Data Scientist Jobs in Springfield, MA

Kemper

Data Science Manager

Hartford, CT · Hybrid

Manages a small team of data scientists and data engineers to research, design, develop, deploy ... Kemper will never request personal information, such as your social security number or banking ...

Cvshealth

Actuarial Corporate Internship

Hartford, CT · Hybrid

$26 - $40/hr

Our Corporate Interns can apply for future full-time roles during the program and have an increased ... Actuarial Science, Analytics, Data Science, Economics, Engineering, Mathematics, Risk Management ...

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All JobsBank Data Scientist JobsInternship Bank Data Scientist JobsInternship Bank Data Scientist Jobs in Springfield, MA

Internship Bank Data Scientist information

See Springfield, MA salary details

$45.8K

$164.4K

$242.6K

How much do internship bank data scientist jobs pay per year?

As of Aug 6, 2026, the average yearly pay for internship bank data scientist in Springfield, MA is $164,441.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,000.00 and $169,400.00 per year, depending on experience, location, and employer.

What does an internship bank data scientist do?

An Internship Bank Data Scientist assists banking organizations in analyzing large sets of financial data to uncover trends, improve decision-making, and enhance services. Their work typically involves cleaning and preparing data, applying statistical models, and creating visualizations to communicate insights. Interns often collaborate with senior data scientists and other departments to support projects related to risk assessment, fraud detection, and customer analytics. This role provides hands-on experience with industry-standard tools and real-world banking data, offering valuable exposure to the field.

What types of projects does an internship bank data scientist typically work on, and how do these projects contribute to the bank's objectives?

Internship Bank Data Scientists often work on projects involving data analysis, predictive modeling, and process automation to support departments like risk management, marketing, and customer analytics. These projects might include developing models to detect fraudulent transactions, segmenting customers for targeted offers, or optimizing internal workflows. Interns collaborate closely with senior data scientists, analysts, and IT teams, gaining exposure to real-world banking datasets and tools. The work completed by interns not only contributes to the bank’s data-driven decision making but also provides valuable, hands-on experience that can lead to future full-time opportunities.

What are the key skills and qualifications needed to thrive as an internship bank data scientist, and why are they important?

To thrive as an Internship Bank Data Scientist, you need a solid understanding of statistics, data analysis, and programming languages like Python or R, often supported by coursework or a degree in data science, mathematics, or a related field. Familiarity with data visualization tools (e.g., Tableau), SQL databases, and machine learning libraries is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret data and convey insights to non-technical stakeholders. These skills are crucial for transforming complex data into actionable strategies that support banking operations and decision-making.

What is the difference between Internship Bank Data Scientist vs Data Analyst?

AspectInternship Bank Data ScientistData Analyst
Required CredentialsTypically pursuing or holding a degree in Data Science, Statistics, or related fieldsOften holds a degree in Data Analysis, Statistics, or related fields
Work EnvironmentInternship setting within financial institutions or banks, focusing on data modeling and analysisVaries from finance to marketing, working with data visualization and reporting
Employer & Industry UsageUsed by banks and financial firms for data-driven decision making during internshipsCommon across industries for interpreting data and supporting business decisions

The Internship Bank Data Scientist role is an entry-level position focused on developing data science skills within banking environments, often as part of an internship program. In contrast, Data Analysts typically work across various industries, focusing on data interpretation and reporting. While both roles require analytical skills and familiarity with data tools, the Data Scientist role emphasizes modeling and machine learning, whereas Data Analysts focus more on data visualization and descriptive analysis.

What are the most commonly searched types of Bank Data Scientist jobs in Springfield, MA? The most popular types of Bank Data Scientist jobs in Springfield, MA are:
What job categories do people searching Internship Bank Data Scientist jobs in Springfield, MA look for? The top searched job categories for Internship Bank Data Scientist jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Internship Bank Data Scientist jobs? Cities near Springfield, MA with the most Internship Bank Data Scientist job openings:
Internship Bank Data Scientist jobs near you

Data Transformation Analyst Intern

Hispanic Health Council Inc

Hartford, CT • On-site

Internship

Re-posted 21 days ago

Job description

About Company:

Since 1978, Hispanic Health Council has been championing health equity promotion and social justice in Connecticut through groundbreaking research and innovative health and human services. Our dynamic, culturally competent team creates lasting change in vulnerable communities through evidence-based programs and advocacy. Through our transformative initiatives, we're making an internationally recognized impact while offering meaningful careers with real growth opportunities. If you're passionate about making a difference, there's a place for you here!


About the Role:

As a Data Analyst Intern, you will play a crucial role in supporting our data-driven decision-making processes by collecting, processing, and analyzing large datasets. This internship offers a hands-on opportunity to apply statistical and analytical techniques to real-world business challenges, enhancing your technical and problem-solving skills. You will be responsible for preparing reports and visualizations that clearly communicate findings to stakeholders at various levels. Ultimately, your contributions will help improve operational efficiency and support strategic initiatives within the organization.

Minimum Qualifications:

  • Currently enrolled in or recently graduated from a degree program in Data Science, Statistics, Computer Science, or Mathematics Program.
  • Proficiencyin Excel, Tableau, and statistical tools (e.g., Python, R).
  • Knowledge of data warehousing and big data frameworks (e.g., Hadoop, Spark).
  • Strong mathematical and analytical skills, with familiarity in predictive modeling.

NOTE- It's an unpaid internship.

Preferred Qualifications:

  • Experience with programming languages such as Python or R for data analysis.
  • Knowledge of SQL for querying databases.
  • Exposure to data visualization tools like Tableau, Power BI, or similar platforms.
  • Understanding of machine learning fundamentals.
  • Previous internship or project experience involving data analytics.

Responsibilities:

  • Extract, clean, and transform data from multiple sources into standardized formats.
  • Develop data dictionaries and streamline metadata documentation for harmonized datasets.
  • Build data visualizations using Tableau and Excel for clarity on project insights.
  • Assist in model creation and validation for AI-driven trends analysis.

Skills:

In this role, you will apply your analytical skills daily to interpret complex datasets and extract meaningful insights that inform business decisions. Proficiency in tools like Excel, SQL, and programming languages such as Python or R will enable you to manipulate data efficiently and automate repetitive tasks. Your ability to create clear and compelling visualizations will help translate technical findings into accessible information for diverse audiences. Strong communication skills will be essential as you collaborate with team members and present your analyses. Additionally, your problem-solving mindset will drive continuous improvement in data processes and contribute to innovative solutions.