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Financial Analytics Intern Jobs in Boston, MA (NOW HIRING)

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Financial Analytics Intern information

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$28

How much do financial analytics intern jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for financial analytics intern in Boston, MA is $21.57, according to ZipRecruiter salary data. Most workers in this role earn between $18.56 and $24.28 per hour, depending on experience, location, and employer.

What is a financial analytics intern?

Financial Analytics Interns are entry-level professionals, typically students or recent graduates, who support financial teams by analyzing data, creating reports, and assisting with financial modeling. They work under the supervision of experienced analysts to gain practical experience in finance-related tasks, such as forecasting, budgeting, and preparing presentations. The role is designed to provide exposure to financial analysis tools, industry practices, and real-world business challenges, helping interns build foundational skills for a career in finance.

What typical projects does a financial analytics intern work on, and how do these projects support the larger finance team?

As a Financial Analytics Intern, you can expect to work on projects such as analyzing financial data sets, creating financial models, preparing reports on budget variances, and assisting with forecasting and trend analysis. These projects help the finance team make data-driven decisions by providing insights on company performance, identifying cost-saving opportunities, and supporting strategic planning. Interns often collaborate closely with analysts, accountants, and managers, gaining exposure to multiple areas of corporate finance while developing practical analytical skills.

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

To thrive as a Financial Analytics Intern, you need strong quantitative skills, proficiency in financial analysis, and basic knowledge of accounting or finance, often supported by coursework in finance, economics, or related fields. Familiarity with Excel, data visualization tools like Tableau, and statistical programming languages such as Python or R is typically expected. Attention to detail, analytical thinking, and effective communication are standout soft skills in this role. These abilities are crucial for accurately interpreting financial data, supporting decision-making, and effectively presenting insights to stakeholders.

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

AspectFinancial Analytics InternFinancial Data Analyst
Required CredentialsTypically pursuing or recent graduate in finance, economics, or related fieldBachelor's or master's in finance, economics, or data analysis
Work EnvironmentInternship programs, entry-level, often in finance or consulting firmsFull-time role in finance departments, investment firms, or consulting
Employer & Industry UsageUsed by companies for training and entry-level supportUsed for ongoing data analysis, reporting, and decision support

The main difference is that a Financial Analytics Intern is an entry-level position for students or recent graduates gaining experience, while a Financial Data Analyst is a full-time professional responsible for analyzing financial data to inform business decisions.

What are popular job titles related to Financial Analytics Intern jobs in Boston, MA?

For Financial Analytics Intern jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Financial Analytics Intern jobs in Boston, MA look for?

The top searched job categories for Financial Analytics Intern jobs in Boston, MA are:

Financial Analytics Intern jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 16 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)