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Data Analytics Intern Jobs in Walpole, MA (NOW HIRING)

Longwood Collective

Power BI Analyst Intern

Boston, MA · On-site

Longwood Collective is seeking an organized and motivated Power BI Analyst Intern for their Area ... This data includes critical demographic, facilities, parking, commuting benefit, financial ...

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All JobsData Analytics Intern JobsData Analytics Intern Jobs in Walpole, MA

Data Analytics Intern information

See Walpole, MA salary details

$13

$24

$45

How much do data analytics intern jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for data analytics intern in Walpole, MA is $24.54, according to ZipRecruiter salary data. Most workers in this role earn between $18.89 and $26.73 per hour, depending on experience, location, and employer.

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

To thrive as a Data Analytics Intern, you need a solid understanding of statistics, data analysis, and proficiency in programming languages like Python or R, often supported by coursework in mathematics, computer science, or related fields. Familiarity with data visualization tools (such as Tableau or Power BI), SQL databases, and spreadsheet software is typically expected. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret data and present findings clearly. These skills are crucial for drawing meaningful insights from data and supporting decision-making processes within an organization.

What are some common challenges data analytics interns face during their internship, and how can they overcome them?

Data Analytics Interns often encounter challenges such as working with large and complex datasets, learning new analytical tools and programming languages on the job, and translating data findings into actionable insights for non-technical stakeholders. To overcome these challenges, interns should proactively seek guidance from mentors, take advantage of available training resources, and communicate regularly with team members to clarify project goals. Developing strong problem-solving skills and being open to feedback also helps interns grow and succeed in the role.

What does a data analytics intern do?

A Data Analytics Intern assists in collecting, processing, and analyzing data to help organizations make informed decisions. They typically work with tools like Excel, SQL, and data visualization software to identify trends, create reports, and support business objectives. Interns often collaborate with data analysts and other team members to gain practical experience and develop their technical skills. Their work may involve cleaning datasets, running basic analyses, and presenting findings to stakeholders.

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

AspectData Analytics InternData Analyst
Required CredentialsTypically pursuing or recent graduate in related fieldBachelor's or higher in data-related field, some certifications
Work EnvironmentInternship programs, entry-level tasks, supervisedFull-time, independent project work, more responsibility
Employer & Industry UsageInternships in various industries, training rolesFull-time roles across industries like finance, tech, healthcare
Common Search & Comparison IntentUnderstanding entry-level opportunities, learning rolesCareer progression, skill development, salary expectations

The main difference between a Data Analytics Intern and a Data Analyst lies in experience, responsibilities, and employment status. Interns are typically students or recent graduates gaining initial exposure, while Data Analysts are full-time professionals handling complex data projects. Internships serve as training grounds, whereas Data Analysts are expected to independently analyze data and contribute to decision-making processes.

Can I do a data analytics intern?

A data analytics intern position is typically available to students or recent graduates with skills in data analysis, statistics, and tools like Excel, SQL, or Python. Applicants usually need to demonstrate analytical abilities and may be required to work part-time or full-time during a specific internship period.
What job categories do people searching Data Analytics Intern jobs in Walpole, MA look for? The top searched job categories for Data Analytics Intern jobs in Walpole, MA are:
What cities near Walpole, MA are hiring for Data Analytics Intern jobs? Cities near Walpole, MA with the most Data Analytics Intern job openings:
Data Analytics Intern jobs near you
Infographic showing various Data Analytics Intern job openings in Walpole, MA as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 10% Part Time, and 8% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $51,037 per year, or $24.5 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted yesterday

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)