Senior Data Scientist

Job Description

Join our Group Functions AI team as a Senior Data Scientist, where you’ll design and operate large scale AI/ML systems that protect customers and prevent financial crime globally. In this role, you’ll own production grade models end to end, influence enterprise AI standards, and collaborate with risk, technology, and data partners worldwide. This is a high impact role for a senior data scientist who thrives at the intersection of advanced modeling, real world deployment, and business outcomes Position Responsibilities: AI/ML Leadership: Architect, build, deploy, and maintain enterprise-grade AI/ML models in production, ensuring reliability, scalability, and observability. Model Operations: Establish best practices for MLOps (CI/CD for ML, monitoring, data/feature pipelines), model governance, and risk controls across large datasets. Advanced Analytics: Lead fraud detection solutions leveraging graph analytics; experience with graph databases (e.g., Neo4j) is a plus. Cloud Platforms: Drive large-scale data processing and model deployment on Azure (e.g., Databricks, Azure ML), optimizing performance and cost. Data Strategy: Oversee complex data exploration, feature engineering, and experiment design to uncover patterns and improve signal quality. Innovation: Evaluate and integrate GenAI and emerging methods to enhance detection efficacy and automation. Stakeholder Engagement: Translate high-level, ambiguous business problems into clear technical requirements; manage executive and cross-functional stakeholder expectations. Communication: Present complex findings in plain English to non-technical audiences; influence decisions with clear narratives and metrics. Program Management: Lead multiple concurrent, high-priority projects; plan roadmaps, manage risks, and deliver measurable outcomes. Mentorship: Coach and mentor junior data scientists, establishing standards for coding, experimentation, and documentation. Global Collaboration: Work across time zones and coordinate with regional teams; flexibility to attend global meetings as needed. Required Qualifications: 5 years of experience building and maintaining enterprise-grade, large-scale AI/ML models in production environments. Advanced degree: Master’s or PhD in Computer Science, Data Science, Statistics, Engineering, or related field. Expert-level Python and strong familiarity with PySpark/Spark SQL/Spark ML; rigorous software engineering practices (testing, code review, modular design). Proven stakeholder management and the ability to translate complex technical topics for non-technical audiences. Demonstrated ability to lead multiple high-priority initiatives and convert vague business asks into clear, actionable technical requirements. Experience with Azure Databricks and cloud-native ML tooling; solid understanding of data pipelines and MLOps. Track record of mentoring and elevating junior team members. Flexibility to collaborate with global teams and attend meetings across time zones. Prefer

Required Skills