Senior Data Analyst

Posted 2 Days Ago
Hiring Remotely in United States
Remote
Senior level
Business Intelligence • Consulting
The Role
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.
Summary Generated by Built In
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
  • 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

Skills Required

  • Advanced degree in a related field such as Data Science, Statistics, or Finance
  • 5+ years of experience analyzing large transactional, customer, or financial datasets for AML, financial crimes, fraud, or investigative analytics
  • Ability to identify suspicious behaviors, emerging typologies, hidden relationships, and anomalous transaction patterns
  • Experience developing, enhancing, and validating AML detection strategies, scenarios, models, or monitoring rules
  • Strong understanding of money laundering methodologies and financial crime typologies
  • Ability to convert investigative findings into defensible detection logic, thresholds, and risk indicators
  • Advanced SQL skills for querying, extracting, manipulating, and analyzing large datasets
  • Strong Alteryx experience, including workflow design, data preparation, aggregation, segmentation, statistical analysis, and investigative exploration
  • Ability to formulate hypotheses, test suspicious activity indicators, and develop evidence-based recommendations
  • Strong communication skills for articulating complex analytical findings
  • Experience designing AML monitoring scenarios or detection models from concept through implementation
  • Experience with lookback analyses, typology development, threshold calibration, segmentation studies, and alert effectiveness reviews
  • Experience using SQL and Alteryx for forensic transaction analysis and financial crime risk identification
  • Familiarity with SAR narratives, AML investigations, regulatory expectations, and suspicious activity identification
  • Experience evaluating transaction networks, customer relationships, and behavioral patterns
  • Knowledge of statistical analysis, anomaly detection, behavioral profiling, and risk-based segmentation
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The Company
HQ: New York, NY
276 Employees
Year Founded: 2009

What We Do

K2 Integrity is the preeminent risk, compliance, investigations, and monitoring firm—built by industry leaders, driven by interdisciplinary teams, and supported by cutting-edge technology to safeguard our clients’ operations, reputations, and economic security. K2 Integrity represents the merger of K2 Intelligence, an industry-leading investigative, compliance, and cyber defense services firm founded in 2009 by Jeremy M. Kroll and Jules B. Kroll, the originator of the modern corporate investigations industry, and Financial Integrity Network (FIN), a premier strategic advisory firm founded by Juan Zarate and Chip Poncy dedicated to helping clients achieve their financial integrity goals. K2 Integrity leverages unmatched multidisciplinary experience to develop cutting-edge solutions, stimulate business opportunities, and shape global economic security in a complex world. Whether it’s protecting clients’ assets or navigating the complex financial regulatory landscape to help clients identify, manage, and mitigate risk, K2 Integrity is an advisor trusted to meet and exceed clients’ goals in a rapidly changing world. To learn more about how K2 Integrity is revolutionizing the management of risk, visit our website, www.k2integrity.com.

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