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Freelance Python Data Analysis Jobs in Massachusetts

MORSE Corp

Data Scientist

Cambridge, MA

Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods * Proficiency in one or more programming languages like Python ...

StepStone Group

Data Analyst II

Newton, MA · On-site

Experience with Python (preferred) or R for data analysis (e.g., pandas, numpy) * Experience with data visualization tools such as Tableau or Streamlit * Advanced Excel and spreadsheet analysis ...

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 ...

STR

Data Scientist (CLEARANCE REQUIRED)

Woburn, MA · On-site

... data analysis pipelines using standard tools (e.g., Python, C++) • Experience designing and implementing experiments to verify and compare algorithm performance with measured data and/or ...

MITRE

Data Analytics

Bedford, MA · On-site

... • Apply analysis skills, including exploratory data analysis, time series analysis, linear ... python or R for data science and modeling • Proficient with code environment management and ...

New

Methods Machine

Sr Data Analyst/Data Analyst

Sudbury, MA · On-site

$74K - $112K/yr

Lead the collection, integration, and analysis of data from CRM, ERP, and other enterprise systems ... Experience with Python, R, or similar analytical programming languages. * Familiarity with ERP/CRM ...

Methods Machine

Sr Data Analyst/Data Analyst

Sudbury, MA · On-site

$74K - $112K/yr

Lead the collection, integration, and analysis of data from CRM, ERP, and other enterprise systems ... Experience with Python, R, or similar analytical programming languages. * Familiarity with ERP/CRM ...

LivaNova

Data Analyst

Boston, MA

$70K - $100K/yr

... analysis, reporting, and visualization support to the Statistics & Data Science team across post ... Strong programming skills in R or Python, with experience in both. Advantageous to be familiar with ...

MORSE Corp

Data Scientist

Cambridge, MA · On-site

$90K - $210K/yr

Solid understanding of data analysis, physics, linear algebra, statistics, algorithms, optimization, and/or machine learning methods * Proficiency in one or more programming languages like Python ...

StepStone Group

Senior Data Analyst

Newton, MA · On-site

$94K - $119K/yr

Proficiency in Python for data analysis (pandas, numpy; scikit-learn is a plus) * Experience with data visualization tools (Tableau, Looker, Power BI, or similar) * Experience with Master Data ...

Citizens

Principal Data Scientist

Boston, MA · On-site

$156K - $194K/yr

Performing exploratory data analysis in Datalake using Python & R; Developing predictive models by implementing data analysis and research, including time series analysis, regression analysis ...

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Freelance Python Data Analysis information

What is freelance Python data analysis?

Freelance Python data analysis involves using the Python programming language to analyze and interpret data for clients on a project or contract basis. Freelancers in this field typically work with datasets to extract insights, visualize results, and help businesses make data-driven decisions. They often use libraries such as pandas, NumPy, and matplotlib, and may work across industries like finance, marketing, healthcare, and technology. Freelancers enjoy flexibility in choosing their projects and clients, and often work remotely.

What are the key skills and qualifications needed to thrive as a Freelance Python Data Analyst, and why are they important?

To thrive as a Freelance Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics and data manipulation, often backed by a relevant degree or proven portfolio. Experience with tools such as Pandas, NumPy, Jupyter Notebooks, and data visualization libraries like Matplotlib or Seaborn is typically required. Excellent problem-solving abilities, communication skills, and the ability to manage projects independently distinguish top performers in this role. These skills enable analysts to deliver actionable insights, meet client expectations, and maintain a successful freelance business.

What are some common challenges freelance Python data analysts face when working with clients remotely?

Freelance Python data analysts often encounter challenges such as clarifying project requirements, managing client expectations about deliverables, and ensuring timely communication across different time zones. Working remotely can also mean troubleshooting data access or security issues, especially if clients have strict data privacy policies. Building trust through regular updates and transparent reporting is key to successful collaborations in this role.
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Freelance Python Data Analysis jobs near you

Ph.D. Graduate Intern Quantitative Portfolio Risk Analytics

Risk Analytics Company

Cambridge, MA

Full-time

Posted 14 days ago

Be an early applicant

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 applyespecially 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 Youll 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)