Top Tech Jobs & Startup Jobs in Mumbai

Manage diligence, risk grading, structuring, and monitoring of a diverse wholesale credit portfolio. Serve as Credit Officer for relationships, perform financial analysis and credit memos, set exposure appetite, approve trading activity, recommend structural mitigants, oversee legal negotiations, maintain credit research, mentor junior staff, lead efficiency projects, and participate in client due diligence.

Support accuracy and integrity of financial records for Global Investment Banking by enforcing controls, supporting month/quarter-end close, investigating variances, ensuring correct booking/treatment, identifying control risks, driving process improvements, and partnering with Finance, Operations, Technology, and regional teams.

Perform credit due diligence and risk assessments, build and challenge financial models, produce credit memoranda with recommendations, manage portfolio exposures, recommend risk mitigants and structures, support transaction execution and system setup, partner with coverage/product teams and senior credit officers, monitor industry risks, and mentor junior staff.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime. Perform end-to-end model lifecycle work (feature engineering, training, validation, calibration, monitoring), support model governance and audits, collaborate with SMEs and MLOps for CI/CD and productionization, deliver interpretable explainability outputs, and incorporate GenAI/LLMs for unstructured text signal extraction.

Design, develop, and maintain production ML solutions for trade surveillance and financial crime use cases. Apply supervised and unsupervised methods, execute model lifecycle (feature engineering, training, validation, monitoring), support model governance, partner with MLOps for CI/CD, deliver explainable outputs, and leverage GenAI/LLMs for unstructured data extraction and summarization.

Support India MLRO in AML transaction monitoring and investigations: review alerts from automated systems, assess suspicious activity, recommend escalation or closure, collaborate with regional teams, support regulatory exams, and contribute to AML policy/process updates. Focus on Corporate/Investment Banking AML typologies and ensuring quality and SLA adherence.

Design and deploy automated FP&A pipelines, validations, reconciliations, and dashboards using Python, SQL, and Databricks. Build finance-ready data models, implement data quality controls, support migration from legacy workflows, perform UAT and stakeholder training, and deliver governed self-service BI views to improve reporting efficiency and decision-making.

Lead enterprise data governance engineering programs across the firm. Manage roadmap and operating model for privacy-centric initiatives (consent, retention, cross-border transfer), oversee engineering delivery, KPIs, dashboards, and executive reporting. Drive adoption of cloud-native data platforms (AWS, Databricks, Snowflake), metadata/catalog/lineage, schema governance, and agentic AI-enabled engineering operating models while establishing governance, security, and reuse-first strategies.

Support CCR risk controls, monitor portfolio thresholds, perform ad hoc risk investigations, drive transformation and automation projects, develop analytical tools (Python/SQL/AI/LLM), and collaborate with Quants, Technology, Product and Credit Officers to strengthen exposure measurement, governance and reporting across derivatives and securities financing products.

Design, develop, back-test and monitor loss-forecasting and wholesale credit stress models for regulatory purposes; handle large panel datasets and collaborate with quantitative researchers and business partners using statistical methods and programming (Python/C++).