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

Crowe

Audit Intern Winter 2027

Boston, MA · On-site

$27 - $42/hr

As an intern in Crowe's Audit and Assurance practice you'll get in-depth exposure to the auditing ... You will use our audit tools and technologies that use advanced analytics, data visualizations and ...

Crowe LLP

Audit Intern Winter 2027

Boston, MA

$27 - $42/hr

As an intern in Crowe's Audit and Assurance practice you'll get in-depth exposure to the auditing ... You will use our audit tools and technologies that use advanced analytics, data visualizations and ...

Crowe

Audit Intern Winter 2027

Boston, MA · On-site

$27 - $42/hr

As an intern in Crowe's Audit and Assurance practice you'll get in-depth exposure to the auditing ... You will use our audit tools and technologies that use advanced analytics, data visualizations and ...

Emerson College

Campus Planning Intern

Boston, MA · On-site

$25/hr

Provide assistance with the analysis of the current space utilization and integrate into master ... Advanced Revit skill level * Basic knowledge of building codes; ability to inspect and determine ...

Emerson College

Campus Planning Intern

Boston, MA · On-site

$17 - $21.75/hr

Provide assistance with the analysis of the current space utilization and integrate into master ... Advanced Revit skill level * Basic knowledge of building codes; ability to inspect and determine ...

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All JobsAdvanced Analytics Intern JobsAdvanced Analytics Intern Jobs in Boston, MA

Advanced Analytics Intern information

See Boston, MA salary details

$9

$18

$26

How much do advanced analytics intern jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for advanced analytics intern in Boston, MA is $18.51, according to ZipRecruiter salary data. Most workers in this role earn between $15.67 and $20.91 per hour, depending on experience, location, and employer.

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

To thrive as an Advanced Analytics Intern, you need strong analytical abilities, a solid understanding of statistics, and proficiency in data manipulation, often supported by coursework in mathematics, statistics, or computer science. Familiarity with tools and programming languages such as Python, R, SQL, and data visualization platforms like Tableau or Power BI is typically required. Effective problem-solving skills, attention to detail, and strong communication abilities help you interpret findings and share insights clearly with stakeholders. These skills ensure you can turn complex data into actionable recommendations, supporting data-driven decision-making within the organization.

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

AspectAdvanced Analytics InternData Analyst Intern
Required CredentialsTypically pursuing or holding a degree in Data Science, Statistics, or related fieldsSimilar educational background, often with focus on data analysis or business intelligence
Work EnvironmentInternships in tech companies, consulting firms, or finance sectors focusing on complex data modelingInternships in various industries analyzing data sets, creating reports, and supporting decision-making
Employer & Industry UsageUsed by organizations emphasizing predictive modeling, machine learning, and advanced data techniquesCommon across industries for routine data reporting and basic analysis tasks

While both roles involve working with data and require similar educational backgrounds, the Advanced Analytics Intern focuses on complex modeling and predictive analytics, whereas the Data Analyst Intern typically handles data reporting and basic analysis. The choice depends on the depth of technical skills and project complexity desired.

What does an advanced analytics intern do?

An Advanced Analytics Intern typically assists in analyzing complex data sets to help organizations make informed business decisions. They use statistical tools, programming languages like Python or R, and data visualization techniques to identify trends, patterns, and insights. Interns may also help clean and prepare data, build predictive models, and present findings to stakeholders. Their work supports teams in areas such as marketing, finance, operations, or product development. The role is ideal for those interested in data science, statistics, and business analytics.

What types of projects can an advanced analytics intern expect to work on, and how do these projects contribute to the overall goals of the team?

As an Advanced Analytics Intern, you can expect to work on projects such as data cleaning, exploratory data analysis, building predictive models, and developing dashboards or data visualizations. These projects often support business decision-making by uncovering trends, optimizing processes, or identifying new opportunities. You’ll typically collaborate with data scientists, business analysts, and stakeholders to deliver actionable insights. This hands-on experience not only sharpens your technical skills but also helps you understand how analytics drives value for the organization.

What cities near Boston, MA are hiring for Advanced Analytics Intern jobs?

Cities near Boston, MA with the most Advanced Analytics Intern job openings:

Advanced Analytics Intern jobs near you
Infographic showing various Advanced Analytics Intern job openings in Boston, MA as of August 2026, with employment types broken down into 20% Internship, and 80% Full Time. Highlights an 80% In-person, and 20% Hybrid job distribution, with an average salary of $38,497 per year, or $18.5 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 8 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)