Project description 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 Solid 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 Other Languages English C2 Proficient Seniority Senior Gurugram India Req VR-119353 AI ML BCM Industry 28 11 2025 Req VR-119353