Quantitative Research Engineer

Quantitative Research Engineer

Seeking a quantitative professional with 3+ years of experience building data and analytical tools within financial markets. The ideal candidate will have strong Python skills, experience with SQL, Power BI, R, and Excel, and exposure to Azure/cloud development. The role combines quantitative modeling, AI-driven tools, data pipelines, and investment research to build practical solutions for internal teams and clients.

Job responsibilities:

• Integrate AI tools into quantitative research, model development, prototyping, and client deliverables.
• Build and maintain Python-based tools and cloud services in Azure, including Azure Functions.
• Develop reliable data pipelines using internal systems, external APIs, and MCP integration's.
• Build and improve statistical, predictive, and quantitative models.
• Partner with development teams to integrate research tools into broader technology platforms.
• Produce data-driven research and analytical across investment and capital markets topics.
• Translate complex quantitative results into clear insights for investment professionals and clients.
• Support Investment Analysts and Consultants with custom analytical requests.
• Stay current on developments in AI, quantitative research, and engineering tools, identifying new ways to apply them.

Job requirements:

• 3+ years of experience in quantitative analytical, research, or data-focused roles.
• Strong Python skills with experience building production-level tools and data pipelines.
• Experience with SQL, Power BI, R, and Excel.
• Hands-on experience deploying applications or workflows in the cloud, ideally Azure.
• Experience using AI coding tools.
• Understanding of quantitative modeling, statistics, and machine learning.
• Familiarity with capital markets, economics, or the investment industry.
• Experience working with data from APIs, internal systems, and multiple data sources.
• Strong problem-solving skills with the ability to build tools end-to-end.
• Bachelor's degree in a quantitative/technical field; advanced degree is a plus.
• Strong communication and collaboration skills with an interest in applying new AI and technology solutions.