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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in quantitative testing and data quality for AI and statistical models within financial crime compliance programs, with strong skills in SQL and Python for data analysis and monitoring. Capable of producing thorough documentation for regulatory compliance and effectively communicating technical results to non-technical stakeholders.
Highest-signal resume keywords
Quantitative TestingData Quality AssuranceSQL ProficiencyPython ProgrammingModel Risk Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Applied StatisticsHypothesis TestingMachine Learning EvaluationData Lineage TracingMonitoring Dashboard Development
Soft Skills
Clear CommunicationCollaboration
Tools & Technologies
SnowflakeDatabricks
Industry Keywords
Financial ServicesFintechRegulatory ComplianceModel ValidationData Engineering
Tech Stack
Tools & technologiesCloudPythonSnowflakeSQL
About the role
Key responsibilities & impact- Own quantitative testing, monitoring, and data quality for AI and statistical models powering financial crime compliance programs
- Design and execute pre-launch and post-launch quantitative testing for AI and ML models
- Perform input data quality, variance, stability, and performance testing for agentic and LLM-based systems
- Produce documentation suitable for independent model validation and regulatory examination
- Build and maintain monitoring pipelines and dashboards tracking model inputs, outputs, and downstream outcomes
- Apply statistical tests to detect model drift and degradation
- Deliver model health readouts to model owners and Compliance leadership
- Own data lineage for compliance-critical data elements
- Design data quality checks and partner with Engineering to trace data from source systems to control consumption
- Write production-quality SQL and Python pipelines
- Diagnose and fix pipeline bugs and lead data migrations supporting external regulatory reporting
- Build detective monitoring scenarios to test compliance controls and validate underlying SQL logic
- Prepare testing evidence, model documentation, and walkthroughs for Internal Audit, model validators, and regulators
- Respond to findings and track remediation to closure
- Collaborate across Compliance, Data Science, and Engineering
Requirements
What you’ll need- 4+ years of experience in data science, model risk, quantitative analytics, or data engineering, ideally in financial services, fintech, or another regulated setting
- Strong grounding in applied statistics, including hypothesis testing, drift and stability measures, sampling, and confidence intervals
- Hands-on experience evaluating ML models, including LLM-based or agentic systems
- Advanced SQL and Python skills
- Experience building monitoring dashboards and working in cloud data environments such as Snowflake or Databricks
- Experience with data lineage tracing and data quality rule design
- Ability to write testing and model documentation that withstands independent review
- Ability to communicate technical results clearly to non-technical compliance stakeholders and auditors
- Responsible use of generative AI with human oversight
- Eligible to work in the United States, as indicated by the “Remote - USA” location and US applicant notices
Benefits
Comp & perks- Equity eligibility
- Bonus eligibility
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)
- Quarterly in-person working sessions (“surges”)
- Reasonable accommodations for individuals with disabilities
- Free compatible screen reader available for applicants needing screen-reading technology