高级数据分析师
Senior Data Analyst
我们正在寻找一位具有敏锐好奇心、善于调查并以假设为导向的法务分析专业人士。成功候选人应能熟练处理包含数百万条记录的数据集,使用SQL和Alteryx进行数据分析,发现隐藏的行为模式。他们应具备将分析从预设需求中拓展出来,独立发现新兴的反洗钱(AML)模式,开发可辩护的检测逻辑,并提升组织的金融犯罪监控能力。该职位为远程工作,位于美国。
职责
- 从概念到实施设计新的反洗钱监控场景或检测模型
- 进行回顾性分析、模式开发、阈值校准、分段研究和警报有效性评估
- 利用SQL和Alteryx执行法务交易分析,识别尚未发现的金融犯罪风险
- 识别和评估交易网络、客户关系和行为模式,以发现未被识别的金融犯罪风险
- 使用统计分析、异常检测技术、行为画像和基于风险的分段方法
- 为可疑交易报告(SAR)叙述、反洗钱调查和监管回应提供支持性的数据分析和文档
要求
- 相关领域的高级学位(如数据科学、统计学、金融)
- 5年以上处理包含数百万条记录的大数据集的经验,用于分析大规模交易、客户或财务数据,以支持反洗钱、金融犯罪、欺诈或调查分析项目
- 通过探索性数据分析,能够识别可疑行为、新兴模式、隐藏关系和异常交易模式
- 具备根据交易活动的法务审查开发、增强和验证反洗钱检测策略、场景、模型或监控规则的经验
- 对洗钱方法有深入了解,包括拆分交易、资金混洗、资金池账户、代理活动、第三方转账、资金快速流动、高风险交易对手等其他金融犯罪模式
- 具备将调查结果转化为可辩护的检测逻辑、阈值和风险指标的能力
- 精通SQL,能够独立查询、提取、操作和分析大型数据集以发现潜在问题
查看英文原文
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.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
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
Originally posted on Himalayas