Senior Vice President, Data Management – Quantitative Analysis Manager

BNY

. Apply quantitative techniques from applied mathematics, statistics, econometrics, and risk modeling to solve business problems, assess risk, and generate insights across Risk & Compliance .

Posted 9/21/2026full-timePune • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data architecture, analytics, and risk compliance, with a strong focus on building scalable digital solutions and enhancing data quality through governance and automation. Proficient in applying quantitative techniques and AI/ML methodologies to drive business insights and improve decision-making processes.

Highest-signal resume keywords

Data ArchitectureRisk And Compliance FrameworksSQL ProficiencyMetadata GovernanceAI/ML Platform Familiarity

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Applied MathematicsStatisticsEconometricsRisk ModelingData Pipeline DevelopmentData WarehousingMachine LearningData GovernanceData Quality ImprovementEnterprise Data Design

Soft Skills

Excellent CommunicationStakeholder Management

Tools & Technologies

PythonSQLAPIsEnterprise PlatformsData LakesStreaming ToolsOrchestration ToolsObservability Tools

Certifications & Qualifications

Relevant Industry Certifications

Industry Keywords

Financial ServicesRisk ComplianceRegulatory ReportingKRI/KCIRCSASurveillance

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Apply quantitative techniques from applied mathematics, statistics, econometrics, and risk modeling to solve business problems, assess risk, and generate insights across Risk & Compliance
Work on AI, GenAI, and machine learning use cases for document intelligence, summarization, classification, knowledge extraction, intelligent search, workflow automation, and advanced analytics
Design and deliver scalable digital solutions across ideation, development, testing, deployment, and continuous improvement
Build and enhance data pipelines, dashboards, UI/UX, and reporting solutions using Python, SQL, APIs, and enterprise platforms
Improve processes, strengthen controls, and build hands-on capabilities across analytics, data, engineering, automation, and emerging technologies
Build and operationalize a centralized calculations service with rules, versioning, and traceability
Build and govern a metadata program covering catalog, lineage, classification, ownership, stewardship, and approval workflows
Improve data quality through CDE governance, validation rules, profiling, anomaly detection, and remediation workflows
Publish data quality scorecards and ownership
Provide executive-ready data health reporting and platform metrics connecting infrastructure performance to business outcomes, risk posture, and regulatory commitments
Maintain decision logs and evidence packs
Align platform strategy with BNY’s strategic pillars

Requirements

What you’ll need

8-10 years in data architecture, platform engineering, analytics or data product leadership
Experience in financial services and Risk/Compliance domains strongly preferred
Strong understanding of risk and compliance frameworks, including KRIs/KCIs, RCSA, issues/actions, surveillance, and regulatory reporting
Expertise in enterprise data design, canonical data forms, vectorization/embeddings, semantic layers, and distributed data systems
Hands-on experience with metadata cataloging, lineage, data governance, and access controls across regulated environments
Familiarity with AI/ML platform components and MLOps/DataOps practices
Track record delivering executive-grade dashboards and reporting at enterprise scale
Proficiency with SQL, data warehousing/data lakes, streaming, orchestration, and observability tools
Familiarity with Python and ML pipelines is advantageous
Excellent communication and stakeholder management skills
Bachelor's degree required
Advanced degree in a quantitative area is a plus
Relevant industry certifications or qualifications are a plus

Benefits

Comp & perks

Highly competitive compensation
Benefits and wellbeing programs
Flexible global resources and tools
Generous paid leaves
Paid volunteer time
Health, personal resilience, and financial wellbeing support