• Design and implement predictive models to analyze and anticipate user behavior • Define and establish data instrumentation, telemetry, and observability standards • Develop frameworks and prototypes for analyzing and optimizing user experiences driven by AI agents • Collaborate with product and engineering teams • Create analytical models and reporting frameworks • Guide experimentation strategies, including A/B testing • Provide technical leadership and recommendations on data architecture and system scalability • Translate ambiguous product questions into structured analytical programs.

• Oversee, lead, manage and provide technical expertise within the assigned complex projects/programs • Provide subject matter expert support, solution management and departmental support for project initiatives and training • Provide fully independent and autonomous leadership of data management services across multiple complex global projects/programs • Liaise with DM Management at regular intervals • Collaborate with internal WCT departments working on the same project • Provide mentorship to other members of the DM department • Participate in sponsor audits, regulatory authority inspections and other third party meetings

• Partner with the Payments team to design and develop foundational datasets, metrics, and analytical frameworks that support product strategy and business decision-making. • Analyze customer behavior, product adoption, and transaction activity to generate actionable insights that improve payment experiences and drive business growth. • Research onchain payments ecosystems, blockchain transaction data, and competitive payment solutions to inform product development and market positioning. • Lead strategic analyses that identify new opportunities for product innovation, operational efficiency, and revenue growth. • Build scalable reporting, dashboarding, and automation solutions using SQL, Python, and business intelligence tools to increase organizational leverage. • Communicate analytical findings through compelling visualizations and data storytelling tailored to technical and non-technical stakeholders, including senior leadership. • Influence product and business strategy by partnering cross-functionally with Product, Engineering, Operations, and Business leaders to drive data-informed decision-making.

• Design and implement robust statistical models and machine learning algorithms for large-scale data analysis and predictive analytics • Lead end-to-end development of data science projects, including hypothesis testing, regression analysis, classification, and forecasting • Collaborate with cross-functional teams to define business requirements, translate them into analytical solutions, and drive measurable impact • Optimize and automate data pipelines using Python, PySpark, and R, ensuring efficient data processing and feature engineering • Develop, validate, and maintain probabilistic graph models and advanced statistical computing frameworks • Utilize industry-leading ML frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn to build, train, and deploy models • Establish rigorous model evaluation and monitoring processes using tools like Great Expectations and Evidently AI • Mentor and guide junior data scientists, fostering technical excellence and continuous learning within the team