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What is the difference between Refinitiv Refinitiv vs Financial Data Analyst?

AspectRefinitivFinancial Data Analyst
Primary RoleProvides financial data, analytics, and market insights using Refinitiv platformsAnalyzes financial data to support investment decisions and reporting
Required SkillsData management, financial software proficiency, market knowledgeFinancial modeling, data analysis, Excel, reporting skills
Work EnvironmentFinancial services, data providers, market research firmsBanks, investment firms, asset management companies
CertificationsOften requires finance or data-related certificationsCFAs, financial modeling certifications often preferred

Refinitiv professionals focus on managing and delivering financial data and analytics platforms, while Financial Data Analysts interpret this data to inform investment decisions. Both roles require strong analytical skills, but Refinitiv roles emphasize platform expertise, whereas Financial Data Analysts focus on data interpretation and reporting.

What are popular job titles related to Refinitiv Refinitiv jobs in Connecticut? For Refinitiv Refinitiv jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Refinitiv Refinitiv jobs in Connecticut look for? The top searched job categories for Refinitiv Refinitiv jobs in Connecticut are:
Refinitiv Refinitiv jobs near you
Infographic showing various Refinitiv Refinitiv job openings in Connecticut as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 67% In-person, 8% Hybrid, and 25% Remote job distribution.

Python Software Engineer - Financial Engineering

Risk Analytics Company

Guilford, CT • On-site

$100K - $205K/yr

Full-time

Posted 11 days ago

Job description

Job Title: Python Software Engineer – Financial EngineeringPosition Overview
We are an Portfolio Risk Analytics Company seeking a highly skilled Python Software Engineer with a strong background in financial engineering to design, develop, and maintain quantitative financial applications. The ideal candidate has experience building analytical tools, pricing models, trading systems, or risk management platforms using Python and modern software engineering practices.
Responsibilities
  • Design, develop, and maintain Python applications for financial analysis and quantitative modeling.
  • Build and optimize pricing, valuation, and risk management models for financial instruments.
  • Develop data pipelines for processing market, economic, and alternative data.
  • Implement and maintain backtesting frameworks for trading and investment strategies.
  • Collaborate with quantitative researchers, traders, portfolio managers, and software engineers.
  • Optimize code for performance, scalability, and reliability.
  • Integrate applications with market data providers, databases, and APIs.
  • Write clean, maintainable, and well-documented code.
  • Develop automated testing and deployment pipelines.
  • Monitor production systems and troubleshoot technical issues.
Required Qualifications
  • Bachelor's, Master's, PhD's degree in Computer Science, Financial Engineering, Mathematics, Physics, Engineering, or a related quantitative field.
  • 3+ years of professional Python development experience.
  • Strong knowledge of object-oriented programming and software design principles.
  • Experience with financial engineering concepts, including:
    • Derivative pricing
    • Fixed income analytics
    • Portfolio optimization
    • Risk management
    • Time series analysis
  • Experience with Python libraries such as:
    • NumPy
    • Pandas
    • SciPy
    • Statsmodels
    • scikit-learn
  • Experience working with SQL databases.
  • Familiarity with REST APIs and cloud platforms.
  • Experience using Git and CI/CD workflows.
  • Strong analytical and problem-solving skills.
Preferred Qualifications
  • Experience developing algorithmic trading systems.
  • Knowledge of stochastic calculus, Monte Carlo simulation, and numerical optimization.
  • Familiarity with financial data providers (S&P, Bloomberg, Refinitiv, ICE, Polygon.io, etc.).
  • Experience with distributed computing or high-performance computing.
  • Knowledge of Docker, Kubernetes, or cloud infrastructure (AWS, Azure, or GCP).
  • Experience with machine learning applied to financial markets.
  • Familiarity with C++, Rust, or Java is a plus.
Technical Skills
  • Python
  • NumPy
  • Pandas
  • SciPy
  • SQL
  • Git
  • Linux
  • Docker
  • REST APIs
  • Financial Modeling
  • Quantitative Finance
  • Risk Analytics
  • Time Series Analysis
Desired Personal Attributes
  • Strong quantitative reasoning
  • Excellent communication skills
  • Attention to detail
  • Ability to work independently and collaboratively
  • Passion for financial markets and technology
  • Commitment to writing high-quality, maintainable software
Nice-to-Have Experience
  • Quantitative research
  • Options pricing
  • Fixed income analytics
  • Portfolio construction
  • Market risk or credit risk systems
  • Backtesting platforms
  • Financial data engineering
  • AI/ML applications in finance