Data Scientist-Senior Associate

Job responsibilities

• Define analytic projects by translating business objectives into clear problem statements, success metrics, and delivery plans.
• Develop analyses and deliverables that align to agreed requirements, timelines, and stakeholder expectations.
• Build datasets, queries, and reusable tables to enable scalable analytics and reporting.
• Create visualizations and decision-support tools that communicate insights to technical and non-technical audiences.
• Recommend actionable performance improvements to clients based on payment and transaction behavior patterns.
• Productionize interactive analytics and AI applications with a focus on resiliency, usability, and supportability.
• Identify opportunities to enhance existing analytics products and propose improvements grounded in data.
• Persistently partner with data owners and platform teams to evolve data models for future analytics and product capabilities.
• Collaborate with unit leaders, end users, and development teams to confirm business value and prioritize work.
• Apply quality assurance, change-control, and testing practices for updates to code, models, and data products.
• Support users by addressing questions, incorporating feedback, and improving documentation and training materials.

Required qualifications, capabilities, and skills

• Bachelor's or master's degree in engineering, computer science, statistics, mathematics, or a related quantitative field.
• Four or more years of experience delivering analytics in a big data environment in a self-directed role.
• Experience using SQL (Snowflake) and Python to build analyses and data products.
• Experience applying generative AI tools or techniques to analytics, automation, or decision-support use cases.
• Understanding of algorithms, data structures, and software engineering fundamentals.
• Demonstrated ability to define key performance indicators (KPIs) and performance metrics from data.
• Experience sourcing, assessing, and shaping data for analysis, including improving data structures and query performance.
• Ability to document analytics requirements, assumptions, and deliverables in partnership with stakeholders.
• Strong communication skills with the ability to present insights clearly to varied audiences.
• Strong problem-solving skills with the ability to translate strategy into measurable deliverables.

Preferred qualifications, capabilities, and skills

• Experience in payments, merchant services, or adjacent transaction-driven industries.
• Experience building and evaluating generative AI solutions (for example, prompt design, retrieval-augmented generation patterns, or model evaluation).
• Experience deploying analytics or AI applications into production with monitoring and support practices.
• Experience building data visualizations and dashboards for business users.
• Experience partnering with product and engineering teams to deliver analytics capabilities on shared platforms.