Manager, Delivery Data Science

Company Information Curinos empowers financial institutions to put customers at the center of every decision. Our AI-first platform transforms proprietary data, advanced analytics and deep financial services expertise into timely recommendations - delivered right where teams work. The result: confident decisions, stronger customer relationships, and lasting, profitable growth. Curinos operates under a hybrid modality and has office locations in New York, Chicago, Boston, Toronto, and London. This role is open to remote candidates based in the Toronto area and able to travel as needed. About the Role We’re building the next generation of marketing personalization leveraging AI, machine learning, experimentation, and adaptive decisioning to ensure the right content reaches the right customer at the right moment. This role sits at the intersection of Delivery Data Science and Product Data Science, helping translate advanced modeling capabilities into measurable client outcomes. We are seeking a Manager, Delivery Data Science to lead the development, validation, and application of machine learning solutions powering client programs on Curinos’s proprietary marketing optimization platform. This individual will serve as a bridge between business strategy and technical execution - partnering closely with Data Science, Product, and Client Success teams to develop optimization strategies, support model governance, and drive analytical insights that improve performance. This role combines hands-on model development, experimentation strategy, and analytics leadership. You will be responsible for ensuring models are designed, validated, monitored, and communicated effectively while helping shape how personalization evolves across our client portfolio. What You'll Do Build and Operationalize Predictive Models Partner closely with the Data Science team to train, test, and deploy ML and AI models, within the model risk standards required by the banking industry, including model bias, disparate impact, AI guardrails, privacy controls, and ongoing monitoring Translate business objectives into modeling frameworks, features, and optimization opportunities Own end-to-end model development and validation including sample adequacy, out-of-time testing, and reproducibility checks before sign-off Extend, and deploy our Reinforcement Learning-based marketing optimization capabilities while following our quality standards for model deployment and monitoring Evaluate model performance and identify opportunities for ongoing improvement Own model monitoring, stability tracking, and performance reporting Help operationalize new modeling approaches within live client programs Design Measurement and Experimentation Frameworks Support the development of experimentation strategies that maximize learning and business impact Ensure test design, audience allocation, and outcome measurement align with modeling objectives Partner with…