Senior Manager, Risk Data Analytics

Your Opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.

The Senior Manager position is an individual contributor role within our Analytics, Strategy, Data, & Solutions (ASDS) team, part of the Financial Crimes Risk Management (FCRM) organization. The team provides data and analytical expertise to FCRM teams and beyond, develops surveillance tools, and creates customer risk solutions. ASDS works closely with teams focused on modeling, model risk, anti-money laundering, enhanced due diligence, compliance, technology, and other areas to ensure a robust, well-coordinated approach to tackling financial crimes.

You will work closely with business partners to identify risks and target illicit behaviors. This position is responsible for analyzing data and providing recommendations to support effective and efficient management of Financial Crimes risk. You’ll leverage advanced analytics, programming, and business acumen to drive impactful solutions. The ideal candidate is a strategic thinker with deep analytical expertise, strong collaboration skills, and a passion for improving financial crime risk surveillance through data, models, and innovation.

What You'll Do: 

• Lead the full lifecycle of AML, sanctions, fraud, and financial‑crime detection models and scenarios, including design, development, tuning, validation, and ongoing performance management.
• Analyze large and complex data sets—identifying, extracting, cleaning, and aggregating data using SQL, Python, and analytical tooling—to uncover trends, patterns, and emerging risks.
• Evaluate and enhance existing AML scenarios and rules, ensuring they target the right behaviors, produce effective alerts, and align with regulatory expectations.
• Develop new detection logic, including rules, scenarios, monitoring frameworks, and features to strengthen risk coverage across traditional and cryptocurrency activity.
• Conduct advanced quantitative and statistical analysis to measure model effectiveness, quantify impacts of changes, and assess performance across multiple AML outputs.
• Build clear, compelling presentations that communicate analytical approaches, methodologies, findings, and recommendations to leadership and business partners.
• Collaborate cross‑functionally with technology, data engineering, FCRM, operations, and model‑risk teams to improve data pipelines, model robustness, and surveillance capabilities.
• Support regulatory, audit, and model‑risk engagements through analysis, documentation, process walkthroughs, and development of required artifacts.
• Design and maintain KPI reporting and monitoring routines to evaluate scenario and model performance, recommending and driving corrective actions where needed.
• Lead crypto‑focused surveillance initiatives, including blockchain‑analytics tool deployment, suspicious‑activity detection, and subject‑matter guidance on crypto‑related risks and regulatory trends.
• Manage projects from ideation through implementation, leveraging agile practices and the SDLC to ensure timely and high‑quality delivery.
• Provide leadership within the analytics organization, mentoring team members, shaping best practices, and supporting team‑wide initiatives and capability building.
• Partner with stakeholders throughout the model and scenario development lifecycle, including testing, implementation, tuning, and post‑deployment monitoring.
• Applicants must be currently authorized to work in the United States on a full-time basis without employer sponsorship.

Please note: this position is M-F, 8am-5pm local time and a hybrid work model. It will be 4 days in-office, 1 day from home, during standard business hours. It is only available in the areas listed. Candidate must reside or be willing to relocate on their own to one of the listed areas. 

What you have

Required Qualifications:

• Experience in AML, Fraud, and/or Sanctions within financial‑crime risk domains.
• 5+ years of experience in financial analysis, data analytics, or business intelligence.
• 5+ years working with data from disparate systems such as Teradata, Oracle, SQL Server, BigQuery, or similar databases.
• 3+ years of experience in banking, brokerage, or broader financial‑services environments.
• Advanced programming proficiency in Python and SQL.
• Demonstrated ability to analyze large, complex data sets, synthesize key insights, recommend actionable solutions, and communicate clearly to leadership and cross‑functional partners.
• Strong foundation in data‑science techniques, model development, and performance diagnostics.
• Ability to translate technical and analytical outputs into clear, actionable business insights for both technical and non‑technical audiences.
• Experience developing risk‑based decision strategies and working with decision engines.
• Familiarity with BSA/AML/Sanctions regulatory expectations and financial‑crime risk‑management principles.
• Experience creating dashboards and visualizations using BI tools.
• Highly effective communicator capable of simplifying complex subject matter for all stakeholders.
• Working knowledge of agile methodologies and the SDLC.
• Strong attention to detail, professionalism, integrity, and a positive, accountable work ethic.
• Proficiency with Excel, PowerPoint, and Microsoft Office applications.
• Bachelor’s degree in Statistics, Mathematics, Economics, Business Analytics, Finance, or a related quantitative field. 

Preferred Qualifications:

• ACAMS or ACFCS Certification
• Knowledge of evolving crypto regulations and enforcement typologies
• Cryptocurrency Certifications, such as ACAMS CCAS or CFCS C2SD
• Experience using SAS
• Experience with internal and external exam groups
• Familiarity with tools such as Chainalysis or TRM Labs is a plus