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Internship Data Analytics Graduate Jobs in Boston, MA

Summer Internship

Newton, MA

$16.50 - $19.75/hr

RSM's summer internship program provides hands-on experience, mentorship and professional ... Data Analytics * Marketing * Finance * Human Resources * Business Development Please submit:

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Internship Data Analytics Graduate information

See Boston, MA salary details

$13

$24

$45

How much do internship data analytics graduate jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for internship data analytics graduate in Boston, MA is $24.45, according to ZipRecruiter salary data. Most workers in this role earn between $18.80 and $26.63 per hour, depending on experience, location, and employer.

What is an Internship Data Analytics Graduate?

An Internship Data Analytics Graduate is a recent graduate or current student who participates in a temporary position focused on analyzing and interpreting data to help organizations make informed decisions. This role typically involves working with data collection, cleaning, and visualization tools, as well as statistical analysis and reporting. Interns in data analytics often gain hands-on experience with software like Excel, SQL, Python, or R, and develop skills that prepare them for full-time roles in data analysis or related fields.

What types of projects and responsibilities can I expect during a Data Analytics Graduate Internship?

As a Data Analytics Graduate Intern, you’ll typically work on projects involving data collection, cleaning, and analysis to support business decisions. You may assist in building dashboards, generating reports, and collaborating with senior analysts and cross-functional teams to identify trends and present actionable insights. Expect to use tools like Excel, SQL, and Python or R, and to participate in team meetings where your findings may directly impact ongoing projects. This hands-on experience not only develops your technical skills but also gives you exposure to real-world business challenges and collaborative problem-solving.

What are the key skills and qualifications needed to thrive as an Internship Data Analytics Graduate, and why are they important?

To thrive as an Internship Data Analytics Graduate, you need a solid understanding of statistics, data analysis, and problem-solving, typically supported by coursework in mathematics, computer science, or related fields. Familiarity with data analytics tools such as Excel, SQL, Python or R, and data visualization platforms like Tableau is commonly expected. Effective communication, attention to detail, and a willingness to learn help interns stand out in collaborative and fast-paced environments. These skills and qualities enable interns to extract meaningful insights from data, contribute to team projects, and support informed decision-making.

What is the difference between Internship Data Analytics Graduate vs Data Analyst?

AspectInternship Data Analytics GraduateData Analyst
Required CredentialsTypically pursuing or recently completed a degree in data analytics, statistics, or related fieldsBachelor's degree in data science, statistics, or related field; some roles prefer or require certifications
Work EnvironmentInternship setting, often part-time or temporary, focused on learning and support tasksFull-time professional role with independent project responsibilities
Employer & Industry UsageUsed by companies for entry-level training, often in tech, finance, or consulting sectorsEstablished role across industries like finance, healthcare, marketing, and technology

The main difference between an Internship Data Analytics Graduate and a Data Analyst is experience and responsibility level. Internships are designed for students or recent graduates gaining practical skills, while Data Analysts are full-time professionals handling complex data projects independently.

What are the most commonly searched types of Data Analytics Graduate jobs in Boston, MA? The most popular types of Data Analytics Graduate jobs in Boston, MA are:

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 23 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)