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Data Analysis Intern Jobs in Needham, MA (NOW HIRING)

ImEx Cargo

Supply Chain Analyst Intern

Peabody, MA · Remote

$100 - $250/mo

As a Supply Chain Analyst Intern, you will assist in analyzing, optimizing, and enhancing supply ... Data Analysis and Reporting: * Collect, analyze, and interpret data related to supply chain ...

Bosch Group

Business Intelligence Intern - Fall

Watertown, MA · On-site

$17.25 - $21.50/hr

Position Summary The Data Analytics team is seeking a graduate intern to support reporting, data validation, documentation, and analytics initiatives. This internship is designed for a graduate ...

DotHouse Health

Volunteer/ Intern

Dorchester, MA · On-site

$15.75 - $21/hr

... review/data analysis, literature review, or operations support. If possible, the project will ... the intern completes by the end of the term which may include a presentation, report/dashboard ...

DotHouse Health

Volunteer/ Intern

Dorchester, MA · Hybrid

$15.75 - $21/hr

... review/data analysis, literature review, or operations support. If possible, the project will ... the intern completes by the end of the term which may include a presentation, report/dashboard ...

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All JobsData Analysis Intern JobsData Analysis Intern Jobs in Needham, MA

Data Analysis Intern information

See Needham, MA salary details

$13

$24

$45

How much do data analysis intern jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for data analysis intern in Needham, MA is $24.52, according to ZipRecruiter salary data. Most workers in this role earn between $18.85 and $26.73 per hour, depending on experience, location, and employer.

What are some common challenges faced by Data Analysis Interns during their internship, and how can they overcome them?

Data Analysis Interns often encounter challenges such as working with large, unstructured datasets and learning to use new analysis tools or programming languages. Navigating ambiguous project requirements and balancing multiple deadlines can also be difficult. To overcome these obstacles, interns are encouraged to proactively communicate with their mentors, seek feedback regularly, and make use of available resources such as online tutorials or internal documentation. Collaborating with teammates and asking questions fosters learning and helps interns efficiently resolve roadblocks.

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

AspectData Analysis InternData Analyst
Required CredentialsTypically pursuing or recent graduate in related fieldBachelor's or higher in data-related field, some certifications
Work EnvironmentInternship setting, entry-level tasks, supervisedFull-time role, more independent responsibilities
Employer & Industry UsageInternships in various industries, educational focusEstablished roles in finance, tech, healthcare, etc.
Common Search & Comparison IntentUnderstanding entry-level opportunities, learning rolesCareer progression, skill requirements

The main difference between a Data Analysis Intern and a Data Analyst lies in experience, responsibilities, and employment status. Interns are usually students or recent graduates gaining initial exposure, while Data Analysts are full-time professionals handling more complex tasks independently. Internships serve as stepping stones toward becoming a full Data Analyst.

What Do Data Analysis Interns Do?

A data analysis intern supports a data analyst while obtaining valuable practical experience to pursue a position in the field. Your responsibilities in this position include delivering data, formatting information, querying databases for sales, marketing, accounting, and other departments, developing and updating reports, and assisting with projects when needed. Your duties also include evaluating analysis systems, collaborating with other teams, responding to requests for analysis, and investigating data discrepancies. You collect information and review the model to offer recommendations.

What does a Data Analysis Intern do?

A Data Analysis Intern assists in collecting, processing, and interpreting data to help organizations make informed decisions. They often use tools like Excel, SQL, or Python to analyze datasets, create visualizations, and generate reports. Interns work under the supervision of experienced data analysts or data scientists, learning to apply statistical techniques and solve real-world business problems. This role provides hands-on experience in data analytics and helps interns develop valuable technical and analytical skills.

What are the key skills and qualifications needed to thrive as a Data Analysis Intern, and why are they important?

To thrive as a Data Analysis Intern, you should have a solid understanding of statistics, data management, and analytical thinking, often supported by coursework in mathematics, statistics, or a related field. Familiarity with tools like Excel, SQL, Python, or R, as well as data visualization platforms such as Tableau or Power BI, is typically expected. Attention to detail, problem-solving abilities, and effective communication help interns interpret data accurately and present insights clearly. These skills are vital for transforming raw data into actionable insights that support business decision-making.
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What job categories do people searching Data Analysis Intern jobs in Needham, MA look for? The top searched job categories for Data Analysis Intern jobs in Needham, MA are:
What cities near Needham, MA are hiring for Data Analysis Intern jobs? Cities near Needham, MA with the most Data Analysis Intern job openings:
Data Analysis Intern jobs near you
Infographic showing various Data Analysis Intern job openings in Needham, MA as of July 2026, with employment types broken down into 83% Full Time, 14% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $50,992 per year, or $24.5 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Posted 20 days ago

Job description

Ph.D. Graduate Intern – Quantitative Portfolio Risk Analytics (Cross-Disciplinary)

Position Overview
We are seeking an exceptional Ph.D. graduate student to join our team as a Quantitative Portfolio Risk Analytics Intern. This role focuses on developing and applying advanced analytical methods to understand portfolio risk, market structure, and complex financial systems.
We are intentionally recruiting from cross-disciplinary, research-driven backgrounds. Doctoral candidates from fields such as physics, astrophysics, math, applied mathematics, statistics, engineering, economics, computer science, quantum computing, biotech, and other data-intensive sciences are strongly encouraged to apply—especially those interested in translating rigorous quantitative methods into real-world financial applications.
Key Responsibilities
  • Develop and enhance quantitative models for portfolio risk, including factor-based and statistical approaches 
  • Analyze large, high-dimensional financial datasets to uncover structure, dependencies, and sources of risk 
  • Design and implement analytical tools and pipelines using Python and SQL 
  • Contribute to model validation, backtesting, and performance evaluation 
  • Collaborate with risk, engineering, and data teams to improve model scalability and data infrastructure 
  • Communicate complex quantitative insights through clear visualizations and technical summaries 
  • Apply advanced methodologies from your discipline (e.g., stochastic modeling, optimization, machine learning, or geometric/topological approaches) to improve risk analytics 
Required Qualifications
  • Currently enrolled in a graduate Ph.D. program in a highly quantitative field (e.g., Math, Applied Mathematics, Physics, Astrophysics, Statistics, Computer Science, Engineering, Financial Engineering, Economics, Biotech or other data-driven disciplines) 
  • Strong foundation in probability, statistics, and numerical methods 
  • Proficiency in Python (NumPy, pandas, or similar) and/or SQL 
  • Experience working with large datasets and implementing quantitative models 
  • Ability to think rigorously about complex systems and translate theory into practical solutions 
Preferred Qualifications
  • Familiarity with quantitative finance concepts (e.g., portfolio theory, factor models, volatility modeling, Value-at-Risk) 
  • Experience with scientific computing, optimization, or machine learning 
  • Background or research in cross-disciplinary areas such as: 
    • Statistical physics, complex systems, or network theory 
    • Applied or computational mathematics 
    • Machine learning or probabilistic modeling 
    • Quantum computing or advanced optimization techniques 
    • Topological data analysis or geometric data methods 
  • Prior research, publications, or project work demonstrating advanced quantitative modeling 
What You’ll Gain
  • Exposure to real-world portfolio risk problems at the intersection of finance and advanced analytics 
  • Opportunity to apply cutting-edge academic methods in a production environment 
  • Collaboration with a highly quantitative, cross-disciplinary team 
  • Experience working with large-scale financial data and modern analytics infrastructure 
  • Mentorship and potential pathway to full-time quantitative roles 
Duration & Compensation
  • Internship: Summer 2026, with potential to extend 
  • Paid internship (competitive, based on experience and location)