Data Scientist II
2 weeks ago
About Northbridge Financial Corporation
Northbridge Financial Corporation is a proud Canadian company, wholly owned by Fairfax Financial Holdings. We operate through our renowned brands: Northbridge Insurance, Federated Insurance, and TruShield Insurance. Recognized as one of Canada's leading property and casualty insurance providers, we are dedicated to understanding our clients' needs and empowering Canadian businesses with a secure and prosperous future.
The Role: Data Scientist II
As a Data Scientist II at Northbridge, you will be a vital part of our team, leveraging your expertise in applied statistics, machine learning, and artificial intelligence to develop innovative business solutions. You'll collaborate closely with stakeholders across the organization, contributing to a data-driven culture that drives informed decision-making.
Your Responsibilities:
- Participate in the entire data science lifecycle, from defining business problems and extracting data to developing models, deploying solutions, and managing ongoing performance.
- Conduct thorough data wrangling and exploratory analysis to uncover valuable insights and patterns within complex datasets.
- Train and evaluate a variety of statistical and machine learning models using both open-source and proprietary software tools.
- Develop robust deployment scripts for both batch and real-time delivery of model outputs, ensuring seamless integration with existing systems.
- Maintain deployed models by monitoring performance, debugging scripts, and implementing necessary updates to ensure optimal accuracy and efficiency.
Your Qualifications:
- Bachelor's degree in Statistics, Mathematics, Computer Science, or a related field.
- 2-4 years of professional experience in developing and implementing applied statistical and machine learning models.
- 2-4 years of experience in data wrangling, feature engineering, and writing SQL queries to integrate data from diverse sources.
- 2+ years of programming experience with SQL and Python/R.
- Strong understanding of operational procedures, workflows, and processing functions.
- Experience with scalable data engineering, software engineering, or MLOps practices is a valuable asset.
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