Conduct forensic analytics for anti-money laundering and financial crime monitoring. Analyze large transactional datasets with SQL and Alteryx, identify suspicious behaviors and emerging typologies, develop and validate detection scenarios, calibrate thresholds, perform lookbacks and segmentation studies, evaluate transaction networks, and support AML investigations, SAR narratives, and regulatory responses.
We are seeking a forensic analytics professional who is naturally curious, investigative, and hypothesis-driven. The successful candidate will be comfortable working directly with datasets containing millions of records, using SQL and Alteryx to explore data and uncover hidden behavioral patterns. They should demonstrate a proven ability to move beyond predefined requirements and independently discover emerging AML typologies, develop defensible detection logic, and enhance the organization's financial crime monitoring capabilities. This contractor position is a remote role in the USA.
Job requirements
Job responsibilities
Job requirements
- Advanced degree in a related field (e.g., Data Science, Statistics, Finance)
- 5+ years of experience working with large datasets containing millions of records to analyze large-scale transactional, customer, or financial datasets in support of AML, financial crimes, fraud, or investigative analytics initiatives
- Demonstrated ability to identify suspicious behaviors, emerging typologies, hidden relationships, and anomalous transaction patterns through exploratory data analysis
- Experience developing, enhancing, and validating AML detection strategies, scenarios, models, or monitoring rules based on forensic review of transactional activity
- Strong understanding of money laundering methodologies, including structuring, layering, funnel accounts, mule activity, third-party transfers, rapid movement of funds, high-risk counterparties, and other financial crime typologies
- Proven ability to transform investigative findings into defensible detection logic, thresholds, and risk indicators.
- Advanced SQL skills with the ability to independently query, extract, manipulate, and analyze large datasets to uncover suspicious activity patterns and support detection model development
- Strong Alteryx experience, including workflow design, data preparation, aggregation, segmentation, statistical analysis, and investigative data exploration across large transaction populations
- Ability to independently formulate hypotheses, test suspicious activity indicators, and develop evidence-based recommendations for detection enhancements
- Strong communication skills with the ability to articulate complex analytical findings
- Experience designing new AML monitoring scenarios or detection models from concept through implementation preferred
- Experience conducting lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews preferred
- Experience leveraging SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks preferred
- Familiarity with SAR narratives, AML investigations, regulatory expectations, and suspicious activity identification preferred
- Experience evaluating transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks preferred
- Knowledge of statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies preferred
Job responsibilities
- Design new AML monitoring scenarios or detection models from concept through implementation.
- Conduct lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews
- Leverage SQL and Alteryx to perform forensic transaction analysis and identify previously unknown financial crime risks
- Identify and evaluate transaction networks, customer relationships, and behavioral patterns to uncover previously unidentified financial crime risks
- Utilize statistical analysis, anomaly detection techniques, behavioral profiling, and risk-based segmentation methodologies
- Provide supporting data analytics and documentation for SAR narratives, AML investigations, and regulatory responses
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Develop complex analytics, reporting, dashboards, data products, and ETL/ELT pipelines supporting Medicare Advantage supplemental benefits. Analyze healthcare data, ensure quality and compliance, translate findings into recommendations, collaborate with stakeholders and vendors, manage concurrent initiatives, improve processes, document solutions, and mentor team members.
Top Skills:
AgileDatabricksEtl/EltPower BIPowershellPythonScrumSnowflakeSQLSQL ServerTableau
Big Data • Fintech • Information Technology • Insurance • Software
Analyze and transform cloud data using SQL, dbt, and Google Cloud; build automated pipelines, data visualizations, validation checks, unit tests, monitoring, and alerts. Partner with engineering teams and enterprise insurance clients to improve data quality, governance, automation, and decision-making. Communicate insights clearly, document technical work, develop insurance domain expertise, and contribute to collaborative reviews and on-call support.
Top Skills:
AirflowBigQueryCi/CdConfluenceDbtGitGCPGoogle Data StudioJIRAJupyter NotebookLucidPower BISQLTableau
Fintech • Real Estate
The Senior Data Analyst gathers business and data requirements, assesses data quality and sources, maintains data dictionaries and lineage, defines KPIs, validates reports, and delivers actionable insights. The role supports data governance, PII protection, integrations, data transformation, platform performance, business continuity, and process improvement. It collaborates with stakeholders and data teams, mentors colleagues, resolves complex issues, and contributes to enterprise data strategy and technology decisions.
Top Skills:
AuroradbCassandraConfluenceData GovernanceData PipelinesData ValidationData WarehousesDynamoDBETLGoogle WorkspaceIbm Db2Itilv4JIRALogical Data DictionariesMemsqlMS OfficeMicrosoft SharepointMicrosoft Sql ServerMongoDBMySQLPostgresRedisScrumSdlcSnowflakeSQL
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
