ZipRecruiter

Log In

1

Data Analytics Graduate Jobs in Boston, MA (NOW HIRING)

MIT Lincoln Laboratory

Data Analyst

Lexington, MA · On-site

Experience with common data analytics and/or modeling techniques (e.g., clustering, time-series ... Strong presentation and communication skills Recent Graduate Hiring Range: $100,200 - $120,000 ...

MIT Lincoln Laboratory

Data Analyst

Lexington, MA

Experience with common data analytics and/or modeling techniques (e.g., clustering, time-series ... Strong presentation and communication skills Recent Graduate Hiring Range: $100,200 - $120,000 ...

MIT Lincoln Laboratory

Data Analyst

Lexington, MA

Experience with common data analytics and/or modeling techniques (e.g., clustering, time-series ... Strong presentation and communication skills Recent Graduate Hiring Range: $100,200 - $120,000 ...

NorthEastern

Graduate Program Coordinator

Boston, MA

$53K - $75K/yr

About the Opportunity Job Summary The Graduate Program Coordinator supports the Multidisciplinary ... Data and Operations * Maintain and analyze engagement-related data, including event participation ...

Td

Data Scientist III - FCRM

Boston, MA · On-site

$96K - $155K/yr

Analytics, Insights, & Artificial Intelligence ATTN: This role is not eligible for TD work visa ... Graduate's degree preferred with either progressive project work experience or * 5+ year of ...

next page

Showing results 1-20

All JobsData Analytics Graduate JobsData Analytics Graduate Jobs in Boston, MA

Data Analytics Graduate information

See Boston, MA salary details

$26

$59

$102

How much do data analytics graduate jobs pay per hour?

As of Aug 1, 2026, the average hourly pay for data analytics graduate in Boston, MA is $59.48, according to ZipRecruiter salary data. Most workers in this role earn between $47.79 and $67.36 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Analytics Graduate position, and why are they important?

To thrive as a Data Analytics Graduate, you need a solid understanding of statistics, data modeling, and analytical techniques, usually supported by a relevant degree in mathematics, statistics, computer science, or a related field. Familiarity with tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is highly valued, and certifications in these can provide an added advantage. Strong problem-solving abilities, attention to detail, and effective communication skills help you distill complex data sets into actionable insights and present findings to diverse stakeholders. These skills are essential for delivering data-driven solutions that support business decisions and foster organizational growth.

What are typical career paths or growth opportunities for a Data Analytics Graduate?

As a Data Analytics Graduate, you often start by supporting more senior analysts with data preparation, exploratory analysis, and report generation. Over time, you can advance to positions such as Data Analyst, Business Intelligence Analyst, or Data Scientist, depending on your interests and ongoing skill development. Many organizations encourage further training and offer mentorship to help you specialize in areas like machine learning, data engineering, or domain-focused analytics. With experience and demonstrated impact, leadership roles such as Analytics Manager or Team Lead become attainable, providing broader responsibilities and strategic input into organizational decision-making.

What is a Data Analytics Graduate job?

A Data Analytics Graduate job is an entry-level role designed for recent graduates with a background in data science, statistics, or related fields. It typically involves collecting, cleaning, analyzing, and visualizing data to help organizations make data-driven decisions. Graduates in this role may work with tools like SQL, Python, Excel, and data visualization software to interpret trends and patterns. They often collaborate with different departments to provide insights that optimize business processes. This role serves as a foundation for more advanced positions in data analytics or data science.

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:
What are popular job titles related to Data Analytics Graduate jobs in Boston, MA? For Data Analytics Graduate jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Analytics Graduate jobs in Boston, MA look for? The top searched job categories for Data Analytics Graduate jobs in Boston, MA are:
Data Analytics Graduate jobs near you
Infographic showing various Data Analytics Graduate job openings in Boston, MA as of July 2026, with employment types broken down into 91% Full Time, 6% Part Time, and 3% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution, with an average salary of $123,712 per year, or $59.5 per hour.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 26 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)