Quantitative Risk - Assistant Vice President

Who we are looking for

This role is an AML Transaction Monitoring Lead Analyst responsible for the continued design, development, testing, implementation, and ongoing monitoring of suspicious activity monitoring models and analytical solutions within the Financial Crimes Compliance function. The position requires a hands-on practitioner who can independently write and review complex SQL, develop Python-based analytical workflows, and apply sound model-development methods to AML transaction monitoring problems, with 3+ years of experience.

The successful candidate will combine quantitative and analytical expertise with practical knowledge of AML transaction monitoring, financial products, customer activity, and regulatory expectations. The role demonstrated that recent hands-on SQL and Python experience, strong AML transaction monitoring knowledge, and practical experience developing, testing, or monitoring quantitative models and the ability to translate AML typologies and business risks into clear, scalable monitoring approaches.

You will help develop effective models, methods, features, and proofs of concept; evaluate data and technology solutions; and document, monitor, and report model performance to key stakeholders. You will also partner with business units, AML subject matter experts, data stewards, technology teams, and operational stakeholders to understand customer and transaction journeys across multiple lines of business and align business priorities with Financial Crimes Compliance requirements.

Why this role is important to us

The team plays an important role in strengthening the organization’s ability to identify, assess, and manage financial crime risk. In this role, you will support the development of practical, transparent, and scalable AML monitoring solutions; coordinate across global stakeholders; and help ensure that model and analytical deliverables are well controlled, clearly documented, and fit for purpose. Success in the role depends on connecting robust technical execution, defensible AML risk coverage, and disciplined model governance.

What you will be responsible for

• Support AML and business stakeholders in the design, development, testing, implementation, documentation, and enhancement of suspicious activity monitoring models and analytical solutions.
• Use SQL hands-on to source, join, reconcile, profile, aggregate, and validate large customer and transaction datasets; investigate data-quality issues; and create reproducible analytical outputs.
• Use Python hands-on to perform data preparation, exploratory analysis, feature engineering, model or rule prototyping, testing, performance analysis, and workflow automation using well-structured, reviewable code.
• Perform model owner or model lead responsibilities, including development documentation, implementation planning, change governance, performance assessment, and ongoing monitoring.
• Translate AML typologies, regulatory red flags, business risks, and operational requirements into model features, scenario logic, user stories, and analytical specifications.
• Conduct data exploration, profiling, feature analysis, segmentation, threshold or parameter assessment, testing, and results interpretation using appropriate quantitative techniques.
• Assess model effectiveness, limitations, assumptions, and performance; develop metrics and evidence to support model governance, challenge, validation, audit, and regulatory review.
• Partner with business, operations, investigations, KYC, sanctions, risk assessment, data governance, model risk management, and technology teams to identify appropriate data sources and monitoring solutions.
• Drive process efficiency and investigative effectiveness through workflow analysis, analytical tool design, automation, and proof-of-concept development.
• Communicate complex analytical findings, risks, and recommendations clearly to technical and non-technical stakeholders, including senior management.
• Maintain high-quality, auditable documentation and support timely remediation of identified model, data, or control issues.
• Provide guidance and technical leadership to analysts and project teams and contribute to the development of consistent AML modeling standards and practices.

What we value

• Strong analytical thinking, problem solving, research, and quantitative reasoning skills.
• Demonstrated ability to work directly with data and code, not only coordinate or oversee technical work.
• Solid understanding of AML transaction monitoring concepts, suspicious activity typologies, customer and transaction risk, and the broader financial crime compliance framework.
• Ability to connect business domain knowledge with data, model design, and monitoring outcomes across financial products and services.
• Ability to produce high-quality work products under regulatory, audit, governance, or management deadlines.
• Sound understanding of model-development principles, including problem definition, data suitability, feature design, method selection, testing, validation readiness, limitations, documentation, implementation controls, and ongoing monitoring.
• Strong written and verbal communication skills, with the ability to explain technical concepts and analytical results in clear business language.
• Demonstrated ownership, sound judgment, attention to detail, and the ability to negotiate, influence, and build consensus across a complex global organization.
• Ability to manage multiple priorities and work effectively with cross-functional and geographically distributed teams.

Education and preferred qualifications

• Bachelor’s degree in a quantitative or related discipline, such as Mathematics, Statistics, Data Science, Computer Science, Economics, Finance, Engineering, or a comparable field; an advanced degree is preferred.
• Three or more years of relevant experience in AML transaction monitoring, quantitative risk, financial crime analytics, data analysis, model development, or a related discipline.
• Demonstrated experience with data analysis, data modeling, risk identification, model testing, or performance monitoring in a regulated financial services environment.
• Advanced, hands-on SQL skills, including complex joins, window functions, aggregations, data-quality checks, reconciliation, and query optimization; candidates should be able to independently develop and troubleshoot production-scale analytical queries.
• Strong hands-on SQL skills and working proficiency in Python or a comparable analytical programming language.
• Experience with large-scale data platforms, cloud or distributed analytics environments, and database technologies; experience with Databricks or similar tools is preferred.
• Prior experience serving as a model owner, model developer, quantitative analyst, or analytical lead is preferred.
• Working knowledge of model risk management, data governance, Agile delivery, and software development lifecycle practices is preferred.
• Practical knowledge of AML transaction monitoring, including customer and transaction risk, suspicious-activity typologies, red-flag-to-logic translation, alert generation, investigations, tuning or calibration, coverage assessment, and regulatory or audit expectations.
• Knowledge of related financial crime areas, including KYC, sanctions, customer risk assessment, investigations, and regulatory reporting, is preferred.
• Experience supporting one or more financial services domains, such as asset servicing, custody, payments, securities, wealth management, or transfer agency, is beneficial.

Salary Range:

$90,000 - $157,500 Annual

The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.

For a full overview, visit https://hrportal.ehr.com/statestreet/Home.

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

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