Digital Asset Transactions Monitoring Lead Analyst, Assistant Vice President

Responsibilities Support AML and business stakeholders with the hands‑on development and documentation of suspicious activity monitoring models Support model owner responsibilities, including involvement in model development, testing, tuning, implementation, and ongoing monitoring Be involved in designing and building features, scenarios, and analytical logic to enhance detection of suspicious digital asset activities Contribute to the development of user stories and requirements to improve monitoring of digital transactions and entities Contribute to improving efficiency in Financial Crimes Compliance processes through development of analytical and investigative tools Work with large datasets and partner with data teams to support data sourcing, transformation, and pipeline design (e.g. ETL processes) Collaborate with broader AML Compliance teams including policy, risk assessment, and KYC teams, ensuring alignment of data and model requirements Support validation and testing to ensure the accuracy and effectiveness of models and processes Requirements 3+ years of experience in suspicious activity monitoring within Financial Crimes Compliance, with proven hands‑on experience in data analysis and/or model development coupled with experience in digital assets Hands‑on experience with SQL, including querying, data manipulation, and working with large datasets is required Working knowledge of Python for data analysis, feature engineering, or model development is required Understanding of cryptocurrency transaction flows, blockchain data, and AML typologies in digital assets, or demonstrated interest in developing expertise in this area is required Familiarity with AML transaction monitoring frameworks, including exposure to model development, scenario design, or alert tuning Experience working with large datasets and data environments (e.g., Databricks, Spark, Snowflake) Experience utilising blockchain analytics tools (e.g., Chainalysis, TRM Labs, Elliptic) is preferred Bachelor’s degree in a quantitative discipline (e.g., Mathematics, Statistics, Computer Science, Finance) or related field; advanced degree preferred #J-18808-Ljbffr Jobtailor