Automation & Data Analytics Senior Associate

What you'll do

• Design, build, and maintain programmatic frameworks for quality assurance testing, sampling, and review processes.
• Develop Python automation tools to generate samples, validate inputs, and track testing coverage.
• Apply statistical techniques like confidence intervals and stratification to support quality assurance conclusions.
• Translate loosely defined testing needs into structured analytical requirements and repeatable workflows.
• Integrate data from internal systems, APIs, and structured data feeds to enable workflow automation.
• Perform data quality checks, exception analysis, and output validation to ensure results are defensible.
• Produce clear documentation of sampling logic, assumptions, and controls for audit and regulatory review.
• Communicate analytical findings, risks, and methodology decisions to both technical and non-technical stakeholders.

What we're looking for

• 3+ years of relevant experience in analytics, quality assurance analytics, risk, controls, financial crime, or operations analytics.
• Bachelor’s degree in Computer Science, Economics, Statistics, Mathematics, Data Analytics, or a related quantitative field.
• Strong Python skills, including scripting, data manipulation, and reusable code development.
• Practical experience applying statistical sampling methodologies, error measurement, and data validation techniques.
• Proficiency with SQL for querying, joining, and analyzing large structured datasets.
• Working knowledge of machine learning concepts and common frameworks, such as anomaly detection or classification.
• Experience integrating data via APIs, structured data feeds, or system-generated datasets.
• Basic UNIX/Linux command line skills.
• Master’s degree in Computer Science, Economics, Statistics, Mathematics, Data Analytics, or a related quantitative field (preferred).
• Experience supporting KYC anti-money laundering, financial crime, risk, controls, audit, or regulatory review processes (preferred).
• Experience with Apache Spark or other distributed data processing tools (preferred).
• Familiarity with Databricks or similar cloud-based analytics platforms (preferred).
• Exposure to generative AI use cases for automation, documentation, workflow efficiency, or quality review support (preferred).
• Experience documenting analytical methodologies for audit, risk, compliance, or regulatory review (preferred).