At a Glance
- Tasks: Design and build AI models to solve complex banking problems.
- Company: Join a leading financial institution focused on innovation.
- Benefits: Hybrid work model, competitive salary, and growth opportunities.
- Other info: Collaborative team environment with a focus on continuous improvement.
- Why this job: Make an impact in AI while working on real-world banking solutions.
- Qualifications: 2+ years in Data Science or AI Engineering with strong ML skills.
The predicted salary is between 108000 - 132000 $ per year.
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 Py Spark.
- Work with graph neural networks / graph-based machine learning where appropriate.
- Build agentic AI solutions using Lang Chain and Lang Graph 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 Py Spark for large-scale data processing.
- Experience with scikit-learn or comparable Python ML libraries.
- Experience building AI agents / agentic AI solutions.
- Strong experience with Lang Chain and/or Lang Graph.
- 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.
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AI Data Science Engineer in Toronto employer: Insight Global
At Insight Global, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As an In-House Commercial Counsel in Mississauga, you will benefit from competitive compensation, comprehensive benefits, and ample opportunities for professional growth while working alongside innovative teams in a fast-paced environment. Join us to make a meaningful impact in the e-commerce and ad tech sectors, where your expertise will be valued and your contributions recognized.
