Manager, Delivery Data Science

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.

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.

• 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

• 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 stakeholders to define success metrics and measurement approaches
• Interpret experimental results and translate findings into actionable recommendations
• Identify opportunities to accelerate learning and improve future model performance

• Analyze customer behavior, campaign performance, and engagement signals generated by the platform
• Develop analytical frameworks that uncover opportunities for growth, optimization, and improved customer experience
• Deliver executive-ready insights and recommendations to both internal and external stakeholders
• Translate complex analytical findings into clear business narratives
• Help articulate the business value of personalization and data-driven decisioning

• Provide technical mentorship and analytical guidance to analysts and senior analysts across the Delivery Data Science team
• Establish best practices for analytics, experimentation, model evaluation, and reporting
• Collaborate effectively with Product, Data Science, Client Success and Engineering teams
• Act as a subject matter expert on personalization analytics and model-driven decisioning

We are looking for candidates who:

• Have 5+…