Data Scientist- Enterprise Fraud

Definity is the parent company to some of Canada’s most long-standing and innovative insurance brands, including Economical Insurance, Sonnet Insurance, Family Insurance Solutions, and Petline Insurance. Our ambition is to be one of Canada’s leading and most innovative property and casualty insurers. We can’t do that without our people, so we embrace and encourage a culture that’s collaborative, ambitious, rewarding, and empowering.
- We offer a flexible, hybrid work experience where employees work from the office and virtually depending on the type of work they are doing and who they are working with. Bring your true self and be a part of our journey. It’s better here.

The Data Scientist leads and supports the development and delivery of high-quality analytical solutions within Enterprise Fraud. The Data Scientist reports to the Director of Enterprise Fraud as a key member of a high-performing fraud analytics team focused on using data-driven decision making to solve business problems.

**What can you expect from this role?**
- Employ a full suite of technical capabilities to perform advanced statistical modeling, machine learning, and data mining techniques to identify and prevent fraudulent activities.
- Propose innovative approaches to improve fraud detection methodologies and actively contribute to the adoption of cutting-edge techniques within the team.
- Independently prepare and present high-quality deliverables, including data visualizations and model interpretations, to communicate project insights to director/executive-level audiences, influencing strategic decision-making related to fraud mitigation.
- Collaborate in the development of analytical solutions for fraud detection, providing support to team members. This includes mentoring and knowledge sharing.
- Independently prepare and present high-quality deliverables, including data visualizations and model interpretations, to communicate project insights to director/executive-level audiences, influencing strategic decision-making related to fraud mitigation.
- Continuously research and evaluate state-of-the-art analytical techniques and tools relevant to fraud detection, sharing knowledge and best practices with team members.

**What you bring to this role?**
- University degree in data science, statistics, computer science, operations research, or a related discipline. Preference to individuals with significant technical expertise gained through analytics self-study.
- Competence in most major areas of data science/analytics. These areas include data wrangling, data visualization, predictive modelling, statistics, machine learning, big data analytics, geospatial analytics, and optimization.
- A proven track record of developing integrated, creative analytical solutions in a business context.
- Demonstrated competence in Python, including experience with ensemble methods (e.g., XGBoost, Gradient Boosting) for classification and regression tasks, clustering algorithms (e.g., K-means, DBSCAN), and dimensionality reduction techniques (e.g., PCA, t-SNE). A strong understanding of model evaluation metrics (precision, recall, F1-score, AUC-ROC) is required. Intermediate understanding of SQL techniques and data modeling.
- Good project management, communication, and problem-solving skills.
- Experience guiding and coaching more junior staff members

Salary range $66,300 - $122,100

**What’s in it for you?**
- Hybrid work schedule for most roles
- Company share ownership program
- Pension and savings programs, with company-matched RRSP contributions
- Paid volunteer days and company matching on charitable donations
- Educational resources, tuition assistance, and paid time off to study for exams
- Focus on inclusion with employee groups, support for gender affirmation surgery, access to BIPOC counsellors, access to programs for working parents
- Wellness and recognition programs
- Discounts on products and services

**Go ahead and expect a lot — you deserve it.**

It’s better here — but don’t take our word for it. Definity was named by Great Place to Work ® as one of the Best Workplaces in Canada for women, for youth, and for inclusion.

**Background checks**

This role requires successful clearance of background checks (including criminal checks and leadership references).

LI-Hybrid