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Commission Python Data Analysis Jobs in Boston, MA

MIT Lincoln Laboratory

Data Analyst

Lexington, MA

... MATLAB, Python, or Julia to create quantitative analysis products and assist project leads in ... Experience with common data analytics and/or modeling techniques (e.g., clustering, time-series ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

... data analysis, or machine learning * Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas, scikit-learn, etc), with experience in other languages a plus

Dlapiper

Sr Data Analyst

Boston, MA · Hybrid

$93K - $117K/yr

Key skills include proficiency in SQL, Python, DAX, advanced data analysis, and strong presentation skills. The role also involves fostering collaboration, driving continuous improvement ...

New

Massgeneralbrigham

HDS Senior Data Analyst

Somerville, MA · On-site

$93K - $118K/yr

Uses programmatic tools such as Python or R to support data QA and exploratory analysis. This includes identifying missing data, detecting outliers, and assessing whether anomalies reflect true ...

Pwc

AIT - AI Data Scientist Manager

Boston, MA

$99K - $297K/yr

... analysis, machine learning, data preparation, experimentation, and model evaluation techniques to develop and validate AI/ML solutions - Utilizing Python, data science libraries, model validation ...

MORSE Corp

Data Scientist

Cambridge, MA · On-site

Responsibilities : • Perform data analysis, test and evaluation of existing machine learning ... Python, C, C++, Java, or MATLAB. • Work with customers, stakeholders, and other vendors to ...

Mass General Brigham

HDS Senior Data Analyst

Somerville, MA · On-site

$93K - $118K/yr

Uses programmatic tools such as Python or R to support data QA and exploratory analysis. This includes identifying missing data, detecting outliers, and assessing whether anomalies reflect true ...

Purple Carrot

Senior Data Analyst

Dedham, MA · On-site

$95K - $115K/yr

Skilled in Python - for advanced analysis and automation, including building and running machine learning models. * Experience with data visualization tools (e.g., Looker, Omni, Sigma). * Strong ...

Purple Carrot

Senior Data Analyst

Dedham, MA · Hybrid

$95K - $115K/yr

Skilled in Python - for advanced analysis and automation, including building and running machine learning models. * Experience with data visualization tools (e.g., Looker, Omni, Sigma). * Strong ...

Purple Carrot

Senior Data Analyst

Dedham, MA · On-site

$95K - $115K/yr

Skilled in Python - for advanced analysis and automation, including building and running machine learning models. * Experience with data visualization tools (e.g., Looker, Omni, Sigma). * Strong ...

Pwc

AIT - AI Data Scientist Senior Associate

Boston, MA · On-site

$72K - $212K/yr

... analysis, machine learning, data preparation, experimentation, and model evaluation techniques to develop and validate AI/ML solutions - Utilizes Python, data science libraries, model validation ...

STR

Data Scientist (CLEARANCE REQUIRED)

Woburn, MA · On-site

... analysis pipelines using standard tools (e.g., Python, C++), including implementing software to identify key metrics for various data sets • Experience designing and implementing experiments to ...

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Commission Python Data Analysis jobs near you
Infographic showing various Commission Python Data Analysis job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Ph.D. Graduate Intern - Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA • On-site

Full-time

Re-posted 2 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)