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Summer Python Sql Jobs in Massachusetts (NOW HIRING)

Sentinel Group

Salesforce/Software Engineer

Wakefield, MA · On-site

$95 - $105/hr

Familiarity with SQL/SOQL and enterprise data integration concepts * Salesforce certifications are ... Programming skills in one or more general‑purpose languages, especially Node.js and Python

Vrtx

People Analytics Senior Manager

Boston, MA · Hybrid

$145K - $218K/yr

Deep expertise in HR data, analytics methodologies, and tools (e.g., Python, R, SQL, Power BI ... Summer and the Winter), educational assistance programs including student loan repayment, a ...

Vrtx

Lab Automation Engineer

Boston, MA

$85K - $128K/yr

... scripting languages (i.e., Python, R, C, C++) and basic familiarity with SQL databases ... Summer and the Winter), educational assistance programs including student loan repayment, a ...

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All JobsSummer Python Sql JobsSummer Python Sql Jobs in Massachusetts

Summer Python Sql information

What is the difference between Summer Python Sql vs Summer Data Analyst?

AspectSummer Python SqlSummer Data Analyst
Required SkillsPython, SQL, data manipulationData analysis, SQL, Excel, visualization
Work EnvironmentProgramming, coding projectsData interpretation, reporting
Industry UsageTech, finance, startupsBusiness, marketing, finance

Summer Python Sql focuses on coding and data manipulation using Python and SQL, often in tech-driven environments. Summer Data Analyst emphasizes analyzing data, creating reports, and visualizations. Both roles require SQL skills, but Python is central to Summer Python Sql, while data analysis tools are key for Summer Data Analyst. They share industry overlap but differ in daily tasks and skill emphasis.

What are the most commonly searched types of Python Sql jobs in Massachusetts?

The most popular types of Python Sql jobs in Massachusetts are:

Summer Python Sql jobs near you

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 14 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)