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 Recent 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. 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 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 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 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 Collaborate effectively with Product, Data Science, Client Success and Engineering teams Have 5+ years of experience in Data Science, Marketing Analytics, Machine Learning, Decision Sciences, or a related field Have experience building, validating, and deploying predictive models in production or client-facing environments Possess strong statistical foundations, including experimentation, hypothesis testing, sampling methodologies, predictive modeling, and causal analysis Demonstrate experience supporting model governance, validation, documentation,



or Model Risk Management processes Are comfortable balancing technical depth with stakeholder communication and business impact Have strong presentation and storytelling skills and can communicate effectively with both technical and executive audiences Enjoy partnering across business, product, and technical teams to drive measurable outcomes Technical Skills Python, SQL, and data manipulation at scale Machine learning and statistical modeling techniques.

Model performance evaluation and monitoring Databricks (highly preferred), AWS, or similar cloud-based analytics environments Git, version control, and collaborative development workflows Advanced PowerPoint and data storytelling capabilities MRM reviews and validation requests are completed efficiently and with high quality Delivery teams are equipped with better tools, frameworks, and modeling capabilities to drive client performance Flexible working options, including home working, flexible hours and part time options, depending on the role requirements – please ask! Competitive annual leave, floating holidays, volunteering days and a day off for your birthday! Regular social events and networking opportunities Employee Assistance Program which provides expert third-party advice on wellbeing, relationships, legal and financial matters, as well as access to counselling services We believe strongly in the value of diversity and creating supportive, inclusive environments where our colleagues can succeed.

We do not discriminate on the basis of race, colour, ancestry, national origin, religion, or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other protected characteristics. #

📌 Manager, Delivery Data Science (Toronto)
🏢 Curinos
📍 Toronto