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Charles Schwab · 9 hours ago

Senior Manager, Risk Data Analytics

US-FL-Orlando

Full-time

Hybrid

Senior Level

$104K/yr - $145K/yr

5+ years exp

Charles Schwab is a financial services company that empowers individuals to make an impact on their careers. The Senior Manager, Risk Data Analytics role involves analyzing data to support the management of Financial Crimes risk and developing surveillance tools to detect illicit behaviors.

Financial Services

No H1B

Responsibilities

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

Qualification

AML experienceData analyticsPython proficiencySQL proficiencyFinancial analysisData visualizationModel developmentRegulatory knowledgeAgile methodologiesMicrosoft OfficeCryptocurrency knowledgeSAS experienceCommunication skillsAttention to detailTeam leadershipProject management

Required

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