Sr. Analyst, Financial Crimes Analytics

** Essential Duties and*
* ** Responsibilities*
* + Write advanced queries to extract, transform, and analyze large datasets from complex databases.

+ Develop and enhance transaction monitoring, screening, and customer risk models.

+ Perform ad hoc and strategic analysis on financial crime trends, customer behaviors, and operational risks.

+ Work with large, sometimes messy, datasets ensuring data quality, consistency, and governance.

+ Create reports for stakeholders, regulators, and internal risk committees.

+ Translate business questions into analytical solutions and communicate findings clearly to non-technical stakeholders.

+ Collaborate with technology teams to define data requirements, optimize database structures, and support analytics infrastructure improvements.

+ Stay current with financial crime threats, emerging typologies, and regulatory expectations.

** Knowledge, Skills, and*
* ** Abilities*
* ** Knowledge*
* ** of*
* + Financial crime risks, including money laundering, sanctions evasion, and regulatory expectations (e.g., BSA/AML, OFAC, FATF).

+ Relational database concepts such as normalization, indexing, partitioning, and query optimization.

+ Data management principles, including data quality, lineage, governance, and privacy standards.

+ Industry-standard financial crimes systems (e.g., transaction monitoring, case management, entity resolution platforms) is a plus.

+ Data Ingestion tools such as Alteryx, AWS Glue, Informatica, etc.

+ Fundamentals of statistics and Machine Learning.

** Skill*
* ** in*
* + Writing complex queries, optimizing performance, and managing large datasets.

+ Scripting in Python, or similar languages to support data extraction and automation efforts.

+ Working across various databases such as Oracle, SQL Server, Redshift, Mongo DB, etc.

+ Conducting descriptive, diagnostic, and trend analysis on structured and semi-structured data.

+ Communicating technical findings clearly to both technical and non-technical audiences.

+ Developing visualization reports using tools like Tableau, Qlik, Power BI, or Python libraries is a plus.

** Ability*
* ** to*
* + Translate ambiguous business questions into structured data analysis projects.

+ Work independently on complex problems while collaborating effectively across teams.

+ Manage multiple projects simultaneously with attention to deadlines, priorities, and accuracy.

+ Think critically and creatively to detect anomalies, emerging risks, and operational inefficiencies.

+ Adapt to rapidly changing regulatory, operational, or organizational environments.

+ Uphold the highest ethical standards when working with sensitive financial and customer data.

** Educational/Previous Experience*
* ** Requirements*
* ** Education/Previous*
* ** Experience*
* + Bachelor's degree (B.A.) from a four-year College or university or equivalent experience in Computer Science, Data Analytics, Business, Finance, MIS or related fields

+ Three (3) or more years' experience working on technical teams in Anti-Money Laundering (AML) compliance, Cyber Investigations/Fraud, enterprise technology and/or analytics in financial services, banking, asset management, Fin Tech, or consulting

+ ~OR ~

+ Any equivalent combination of experience, education, and/or training.

** Licenses/Certifications*
* + Amazon Web Service (AWS) certifications are a plus but not required.