• Work cross-functionally to perform source-to-target mappings between incoming data (ex. EHR) and our data model. • Help develop scalable models to automate mapping source-to-target data. • Evaluate and validate data from various sources to ensure accuracy, completeness, and reliability. • Contribute to the development and extension of ontologies, vocabularies, and data standards that underpin our platform. • Identify and evaluate informatics tools, databases, and content sources to enhance the product user experience. • Perform quality control checks and become proficient in querying data stored in our regulatory-grade platform. • Provide critical input into the design of data architectures, algorithms, and analysis workflows.

• Lead and mentor a high-performing data science team operating at the intersection of blockchain, intelligence, and machine learning — balancing individual execution with strategic vision. • Drive technical innovation across a diverse stack (e.g., Airflow, BigQuery, Kafka, Python), ensuring our data models and pipelines scale with quality and precision. • Collaborate cross-functionally with engineering, product, and intelligence teams to transform raw blockchain data into insights that power TRM’s products and customer experiences. • Help make TRM the market leader in blockchain Attribution, setting new standards for accuracy, trust, and usability in blockchain data. • Recruit, develop, and retain top talent — and play a critical role in growing the team’s technical and product maturity.

• Own end-to-end attribution for a risk category, build algorithms and ship to production. • Collaborate closely with SMEs and become a Subject Matter Expert for your category. • Navigate intelligence layers to uncover patterns competitors can't replicate. • Ship production-quality code and drive measurable outcomes, such as tracing illicit funds.

• Partner with Digital Product teams to align analytics and test/learn agendas with strategic priorities for business and enterprise • Translate business strategies into structured measurement approaches, including KPIs, success metrics, and hypotheses for experimentation • Proactively identify opportunities to enhance digital experience, engagement, and value creation through analytics • Support prioritization of digital investments by grounding decisions in data, performance insights, and expected business impact • Evaluate effectiveness of digital capabilities and recommend enhancements, optimizations, and new feature opportunities • Perform deep dives into performance drivers, including adoption, engagement, friction points, and leakage across journeys • Create, operationalize, and evangelize frameworks for segmentation, behavioral, and journey analysis to identify areas of opportunity • Develop and advance analytical approaches from one-time analyses to repeatable, scalable frameworks and data products • Identify key drivers of customer satisfaction, engagement, and value perception across digital experiences • Translate complex analytical findings into clear, compelling narratives that inform business strategy and enable sustained impact across enterprise • Provide strategic input into prioritization, roadmap decisions, and investment tradeoffs • Work across enterprise to incorporate analytics products and insights into enterprise strategic priorities and business growth plans