Principal Data Scientist-Payments-Executive Director
Role details
Job location
Tech stack
Job description
Ignite your passion for product innovation by leading customer-centric development, inspiring solutions, and shaping the future with your strategic vision and influence.
Treasury teams are under pressure to make faster decisions with better data-without increasing risk. In this role you will drive the data science and AI efforts that help shape the future of the corporate treasury.
As a Principal, Data Scientist in the Payments Data & Analytics organization you will partner with the product organization in developing and scaling agentic, AI-native treasury products, grounded in real practitioner workflows., * Define and drive the AI strategy for client facing agentic corporate treasury solutions, identifying high-value opportunities for generative AI, agentic AI, and analytics innovation to create competitive advantage
- Partner with Data, Product, and Technology to deliver AI and machine learning solutions from ideation and prototyping through production deployment, ensuring solutions are scalable, responsible, and aligned to business needs
- Stay current on emerging AI and machine learning techniques and translate new capabilities into practical applications for the Payments business
- Drive evaluation frameworks, experimentation (including A/B testing and causal inference), and strategies that improve client experience
- Attract and retain top analytics talent through hiring, onboarding, and skills development programs.
Requirements
- PhD in a quantitative discipline (e.g., computer science, data science, statistics, econometrics, or related) with 10+ years of progressive analytics and data science experience spanning both hands-on development and enterprise-scale leadership responsibilities
- Deep technical expertise across applied data science, including predictive modeling, statistical analysis, customer/behavioral segmentation, and experimental design, with the ability to coach others and establish engineering-quality standards for analytic work
- Languages & Modeling skills: Python, JavaScript, PHP, SQL, C#, Predictive & Causal Modeling
- AI/ML Platform expertise: MLOps (MLFlow, Metaflow, DataRobot), Generative AI, AI Observability, NLP
- Proven track record translating machine learning and analytics into measurable business outcomes, including defining the decision to be improved, building the model/measurement approach, and driving adoption through product, operations, and executive stakeholders
- Strong strategic and commercial acumen, with the ability to frame ambiguous analytical questions into executable roadmaps and translate findings into executive-ready narratives, trade-offs, and recommendations
- Experience leading analytics across multiple concurrent business domains (e.g., product, customer lifecycle, operations, growth, or planning), balancing near-term delivery with longer-term capability building (data foundations, tooling, and reusable methods)
- Exceptional stakeholder management and communication skills, including influencing senior leaders, aligning cross-functional partners, and managing competing priorities while maintaining trust and momentum
Preferred qualifications, capabilities and skills:
- Experience applying analytics to global scale, B2B digital products and lifecycle management, including acquisition, onboarding, engagement/retention, segmentation-driven personalization, and monetization decisioning
- Exposure to modern generative AI approaches (e.g., large language models, retrieval-augmented generation patterns, and workflow/agent concepts), with the ability to evaluate feasibility, risk, and business value even when not acting as the primary model developer
- Practical experience with causal inference and experimentation at scale, including A/B testing, uplift measurement, and designing experiments that work within real-world product and operational constraints
- Familiarity with responsible AI principles and analytics governance (e.g., model risk management concepts, documentation, monitoring, and bias/robustness considerations), with the judgment to operate effectively in more regulated or higher-reputational-risk environments
- Demonstrated ability to drive analytics adoption through organizational enablement, such as self-service measurement tools, standardized metric definitions, data stewardship practices, and change management for new decision processes
- Comfort operating in Agile/product-oriented delivery models, partnering with product and engineering teams to translate business problems into iterative roadmaps and measurable releases
Benefits & conditions
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.