Senior Quant Developer

4 - 7 years

15 - 19 Lacs

Posted:2 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Project description
  • We need a Senior Quant Developer to work for a leading investment bank client for the part of Trade Surveillance Team. Lead the design and development of advanced quantitative and AI-driven models for market abuse detection across multiple asset classes and trading venues. Drive the solutioning and delivery of large-scale surveillance systems in a global investment banking environment, leveraging Python, PySpark, big data technologies, and MS Copilot for model development, automation, and code quality. Play a pivotal role in communicating complex technical concepts through compelling storytelling, ensuring alignment, and understanding across business,compliance, and technology teams. Responsibilities
  • Architect and implement scalable AI/ML models (using MS Copilot, Python, PySpark, and other tools) for detecting market abuse patterns (e.g., spoofing, layering, insider trading)
  • across equities, fixed income, FX, and derivatives.
  • Collaborate closely with consultants, MAR monitoring teams, and technology stakeholders to gather requirements, share insights, and co-create innovative solutions.
  • Translate regulatory and business requirements into actionable technical designs, using storytelling to bridge gaps between technical and non-technical audiences.
  • Develop cross-venue monitoring solutions to aggregate, normalize, and analyze trading data from multiple exchanges and platforms using big data frameworks.
  • Design and optimize real-time and batch processing pipelines for large-scale market data ingestion and analysis.
  • Build statistical and machine learning models for anomaly detection, behavioral analytics, and alert generation.
  • Ensure solutions are compliant with global Market Abuse Regulations (MAR, MAD, MiFID II, Dodd-Frank, etc.).
  • Lead code reviews, mentor junior quants/developers, and establish best practices for model validation and software engineering, with a focus on AI-assisted development.
  • Integrate surveillance models with existing compliance platforms and workflow tools.
  • Conduct backtesting, scenario analysis, and performance benchmarking of surveillance models.
  • Document model logic, assumptions, and validation results for regulatory audits and internal governance. Skills
  • Must have
  • Technical

    Skills:
  • 7+ years of experience
  • Investment banking domain experience
  • Advanced AI/ML modelling (Python, PySpark, MS Copilot, kdb+/q, C++, Java)
  • Must be well versed with SQL and have hands on experience writing SQL (preferably Spark SQL) that is productionized (not ad-hoc queries) for at least 2-4 years
  • Familiarity with Cross-Product and Cross-Venue Surveillance Techniques particularly with vendors such as TradingHub, Steeleye, Nasdaq or NICE
  • Statistical analysis and anomaly detection
  • Large-scale data engineering and ETL pipeline development (Spark, Hadoop, or similar)
  • Market microstructure and trading strategy expertise
  • Experience with enterprise-grade surveillance systems in banking.
  • Integration of cross-product and cross-venue data sources
  • Regulatory compliance (MAR, MAD, MiFID II, Dodd-Frank)
  • Code quality, version control, and best practices.
  • Soft

    Skills:
  • Strong storytelling and communication for technical and non-technical audiences
  • Collaboration with consultants, MAR monitoring teams, and technology stakeholders
  • Stakeholder management and requirements gathering
  • Leadership, mentoring, and team guidance
  • Problem-solving and critical thinking
  • Adaptability and continuous learning
  • Nice to have
  • Understanding of Financial Markets Asset Classes (FX, FI, Equities, Rates, Commodities & Credit), various trade types (OTC, exchange traded, Spot, Forward, Swap, Options) and related systems is a plus
  • Surveillance domain knowledge, regulations (MAR, MIFID, CAT, Dodd Frank) and related Systems knowledge is certainly a plus
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