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Tier-1 bank, popular Python backend role in a metro increases candidate competition.
Strong banking market-risk and quantitative Python requirements reduce cross-industry transferability.
Explicit 12+ years, mandatory Python, distributed systems, and market-risk/quant domain make filters very strict.
Lead architecture, design, and hands-on development of scalable, resilient, and high-performance Python applications and platforms for quantitative computation and market risk.
Own technical initiatives end-to-end, including planning, governance, budgeting, and enforcing SDLC best practices across globally distributed teams.
Collaborate closely with Risk Managers, Quants, Front Office, DevOps, and Production Support in a matrixed global environment, delivering robust solutions aligned with enterprise standards.
12+ years of hands-on Python application development experience focused on advanced Python 3.x, data structures, algorithms, and distributed systems architecture.
Deep expertise in Python frameworks (FastAPI, Django, Flask), relational and NoSQL databases, Unix/Linux OS, DevOps tools (Docker, Kubernetes, CI/CD pipelines), and testing frameworks (Pytest, unittest).
Experience delivering quantitative, market risk, and stress testing solutions, with exposure to risk methodologies such as VaR and sensitivities.
Work Experience Required: 12+ years; Notice Period: Not explicitly mentioned in the JD.
Technical leader with proven ability to deliver complex, regulated financial technology projects, especially in market risk or stress testing domains.
Strong collaborator skilled in managing cross-functional and global stakeholder relationships including Risk, Front Office, and DevOps teams.
Experienced in advanced quantitative Python development combined with cloud and AI/ML integration to optimize workflows and enhance software capabilities.