Data Scientist

Northbridge Financial Corporation is seeking a Data Scientist to join its Toronto, Ontario team. In this role you will partner with business units to design, build, and deploy predictive and prescriptive analytics solutions.

Key Responsibilities

• Collaborate with stakeholders to define analytical objectives and translate business problems into data‑driven solutions.
• Extract, clean, and transform large, complex datasets from internal and external sources.
• Develop, test, and fine‑tune statistical, machine‑learning, and AI models using Python, R, or similar tools.
• Validate model performance, conduct feature engineering, and ensure robustness across diverse scenarios.
• Deploy models into production environments and monitor their performance over time.
• Communicate findings and actionable insights through visualisations, reports, and presentations to both technical and non‑technical audiences.
• Stay current with emerging data‑science techniques and recommend best practices.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 2+ years of professional experience applying statistical methods and machine‑learning algorithms to solve business problems.
• Proficiency in Python, R, SQL, and data‑visualisation libraries (e.g., Matplotlib, Tableau, Power BI).
• Experience with cloud platforms (AWS, Azure, GCP) and model‑deployment frameworks.
• Strong analytical mindset, problem‑solving skills, and ability to work independently or in a team.
• Excellent written and verbal communication skills.

Preferred Experience

• Knowledge of deep‑learning frameworks such as TensorFlow or PyTorch.
• Familiarity with big‑data technologies like Spark or Hadoop.
• Financial services background or experience with risk, fraud, or customer‑behaviour modelling.

Frequently Asked Questions

What type of projects will I work on as a Data Scientist at Northbridge?

You will work on a variety of projects, including predictive risk modelling, customer segmentation, fraud detection, and AI‑driven business optimization.

What technical skills are essential for this role?

Proficiency in Python or R, SQL, machine‑learning libraries, data‑visualisation tools, and experience with cloud‑based model deployment are essential.

Is prior experience in financial services required?

While not mandatory, experience in financial services or related domains is preferred and helps you understand the business context faster.