AI Data Science Engineer
Summary
Hybrid data scientist + ML engineer role, staffed through Insight Global, building and productionizing AI/ML models for a commercial banking and underwriting team in Toronto. Day to day: translating business problems into ML problems, developing LLM-based agentic workflows with LangChain/LangGraph, and optimizing models with Python, PySpark, and AWS.
We are seeking an AI Data Science Engineer to join a team focused on developing and productionizing advanced AI and machine learning solutions for Commercial Banking and underwriting.
This is a hybrid Data Scientist + AI/ML Engineer role. The ideal candidate can take an ambiguous business problem, translate it into a mathematical/data science problem, build the appropriate model, and then help bring that solution into production.
Key Responsibilities
- Design, build, and productionize AI and machine learning models.
- Develop AI agents and agentic workflows using modern LLM frameworks.
- Build solutions supporting commercial underwriting and prospect scouting.
- Apply traditional machine learning, deep learning, and graph-based modeling techniques to complex business problems.
- Develop and optimize models using Python and PySpark.
- Work with graph neural networks / graph-based machine learning where appropriate.
- Build agentic AI solutions using LangChain and LangGraph within AWS environments.
- Take high-level or abstract business concepts and translate them into mathematical, analytical, and technical solutions.
- Partner with business and technical stakeholders to move AI solutions from concept → model development → production.
- Evaluate model performance and continuously improve AI/ML solutions.
REQUIRED SKILLS AND EXPERIENCE
- 2+ years of hands-on Data Science, Machine Learning, or AI Engineering experience.
- Experience building machine learning models from scratch.
- Strong understanding of traditional ML methodologies.
- Experience with deep learning.Hands-on experience building and productionizing AI/ML models.
- Experience with PySpark for large-scale data processing.
- Experience with scikit-learn or comparable Python ML libraries.
- Experience building AI agents / agentic AI solutions.
- Strong experience with LangChain and/or LangGraph.
- Experience developing AI/ML solutions within AWS.
- Strong problem-solving and critical-thinking skills, especially the ability to translate an abstract business problem into a structured mathematical or ML problem.
NICE TO HAVE SKILLS AND EXPERIENCE
- Banking experience
Artificial intelligence tools are used to assist in screening and assessing applicants for this position.
Vacancy: This posting is for a currently vacant role, and the successful candidate will be hired into an existing open position.