Senior Quant Developer: Python/SQL, Hybrid NYC

MI Softech Inc; New York (NY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

MI Softech Inc seeks a Senior Quant Developer with strong Python programming and SQL skills to support investment banking initiatives in New York, NY. Hybrid role requiring three onsite days weekly and a long-term contract. Face-to-face interview is mandatory.

The ideal candidate brings extensive experience in quantitative development, working with financial data, and collaboration with research, trading, and risk teams.

Qualifications

• 15+ years of overall professional experience.
• Advanced Python programming skills.
• Strong SQL skills and experience with complex financial datasets.
• Investment banking or capital markets domain experience.
• Experience with quantitative models, financial analytics, or risk-related applications.
• Strong problem-solving, analytical, and communication skills.

Responsibilities

• Develop, enhance, and maintain quantitative applications and financial models using Python.
• Write complex SQL queries for financial data processing, analysis, and validation.
• Collaborate with quantitative analysts, traders, risk managers, and technology teams.
• Support quantitative analytics, financial calculations, and model implementation.
• Optimize application performance, data processing, and computational workflows.
• Ensure accuracy, reliability, and consistency of financial data and quantitative outputs.
• Troubleshoot complex technical issues and support production applications.
• Participate in technical design, code reviews, testing, and implementation activities.

Skills

Python programming

SQL

Quantitative analytics

Financial data handling

Problem solving

Communication skills

Job description

MI Softech Inc seeks a Senior Quant Developer with strong Python programming and SQL skills to support investment banking initiatives in New York, NY. Hybrid role requiring three onsite days weekly and a long-term contract. Face-to-face interview is mandatory.

The ideal candidate brings extensive experience in quantitative development, working with financial data, and collaboration with research, trading, and risk teams.