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Manager, Delivery Data Science

Job in Toronto, Ontario, C6A, Canada
Listing for: Curinos
Full Time position
Listed on 2026-08-10
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
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 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
Deliver Advanced Analytics and Strategic Insights     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
Support Team Development and Cross-Functional Collaboration     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
Desired Skills & Expertise   We are looking…
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