The successful candidate will own the end-to-end data model lifecycle, ensuring accuracy, regulatory alignment, and continuous improvement.
Job Objective:
Proactive data-quality checking + data profiling + data-issue identification/management before data reaches AML models.
The project is centered around AML data models and improving the quality of the data feeding those models.
The objective is to identify and resolve data problems before they reach the model, rather than discovering them after the model has consumed the data.
Model and Data Ownership
" Demonstrated accountability for analytical or quantitative models across implementation, maintenance, and controlled change processes.
" Experience operating within governed environments requiring formal documentation, controls, and audit readiness.
" Ability to independently challenge model assumptions and interpret outputs without serving as primary model developer.
" Proficient in performing data analysis and validation using SQL in Teradata environments.
" Ability to analyze large datasets to identify trends, issues, and insights supporting business decisions.
" Experience monitoring, validating, and reporting on data quality metrics including accuracy, completeness, and timeliness.
" Strong capability to conduct root cause analysis for data quality issues.
" Demonstrated experience partnering with stakeholders to drive resolution of data defects and control gaps.
" Proven experience managing complex projects with multiple stakeholders across technology, data, and business teams.
" Ability to coordinate timelines, deliverables, dependencies, and risk issues to successful completion.
Additional Skills:
" 7+ years of experience in analytics, model development
" Bachelor s degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Economics); advanced degree preferred.
" Proven experience as a model owner or developer for financial crimes or AML models.
" Strong proficiency in SQL and Python
" Familiarity with big data tools; experience working with large financial institution data, meaning high-volume, complex datasets such as transactions, customer profiles, and product transactional information that require advanced tools and techniques for analysis.
" Ability to clearly and accurately articulate complex issues, risks, and propose solutions to various levels of staff and management through excellent verbal, written, and interpersonal communication skills.
Knowledge of AML transaction monitoring and regulatory requirements (BSA, USA PATRIOT Act) preferred.
" Familiarity with Oracle Platforms preferred.
EEO:
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.