Data Scientist

Description

At CI, we see a great place to work as one that is a safe place for everyone to have a voice, where people are empowered to take ownership over meaningful work, where there is an opportunity to grow through stretching themselves, where they can work on innovative products and projects, and where employees are supported and engaged in doing so.
CI Financial is seeking a skilled and curious
Data Scientist
to join our Data, AI & Analytics (DNA) team. This role focuses on the
applied use of Generative AI and Agentic AI, leveraging existing large language models (LLMs) and platforms—not building models from scratch. You’ll help design intelligent applications and automation tools that use LLMs to solve business problems, improve workflows, and enhance decision-making.
KEY RESPONSIBILITIES:
Applied Generative & Agentic AI:

• Build intelligent systems and applications using existing LLMs (e.g., OpenAI, Claude, Gemini etc.) through API integration, prompt engineering, fine-tuning, or Retrieval-Augmented Generation (RAG).
• Design and prototype agentic AI systems that can perform multi-step reasoning, task decomposition, and tool use to automate and support business workflows.
• Collaborate with engineering, and analytics teams to identify use cases where Generative AI can provide real business value.

• ML Solution Development & Deployment:

• Develop traditional machine learning models (e.g., classification, regression, clustering) to support forecasting, segmentation, and business intelligence initiatives.
• Collaborate with data engineers and developers to deploy models in production environments using Snowflake, cloud platforms, and APIs.
• Ensure models are accurate, interpretable, and aligned with business outcomes.

Data Exploration & Engineering:

• Work extensively with Snowflake for data querying, transformation, and model input preparation.
• Conduct data profiling and feature engineering on both structured and unstructured data to support ML and GenAI use cases.

Model Monitoring & Improvement:

• Monitor the performance and usage of deployed AI/ML systems.
• Iterate and improve models and LLM-powered tools based on performance metrics and user feedback.

Innovation & Best Practices:

• Stay current with advancements in Generative AI, multi-agent systems, and LLM tooling.
• Share knowledge and support team-wide best practices around experimentation, reproducibility, and responsible AI.

WHAT YOU CAN EXPECT FROM US
Our dedication to the Employee Experience at CI is aimed at supporting, empowering and inspiring our talented team through:

• Recognition & Compensation
• Training & Development
• Health & Well-being
• Communication & Feedback