Senior Data Specialist, Enterprise Fraud Analytics

Definity Insurance Company • Toronto, ON

2h • CA$73,500 - CA$123,500 • Hybrid

About The Position

Reporting to the Manager, Enterprise Fraud, the Senior Data Specialist is a core member of the Enterprise Fraud Analytics team. This hybrid role bridges the gap between data engineering and data science, focusing on architecting scalable data pipelines and designing advanced AI/ML models to detect and prevent insurance fraud. The candidate will also support Enterprise Fraud strategic priorities and support Fraud Savings initiatives. Operating in a highly collaborative environment, this role works alongside Business Analysts and the Special Investigations Unit (SIU). The Senior Data Specialist will heavily leverage Google Cloud Platform (GCP), BigQuery, Vertex AI, and Gemini. This role is critical in transforming complex fraud detection requirements into robust datasets and extracting predictive signals from unstructured text and claims data, ensuring both architectural scalability and mathematical rigor.

Requirements

• University degree in Computer Science, Data Science, Software Engineering, or a related quantitative discipline.
• 3-5 years of professional experience in a relevant role.
• Advanced proficiency in SQL and Python (pandas, scikit-learn) for complex data extraction, data processing, and/or model development.
• Familiarity in modern cloud data warehousing and ML platforms, with Google Cloud Platform (BigQuery, Vertex AI) and orchestration tools (e.g., Airflow, dbt) strongly preferred.
• Experience with Natural Language Processing (NLP), text classification, and Large Language Models (LLMs) / prompt engineering.
• Strong understanding of the ML lifecycle and version control systems.
• Experience implementing Explainable AI (XAI) techniques to translate complex model decisions to business stakeholders.

Nice To Haves

• Master’s degree is an asset.
• Insurance industry knowledge, Fraud Risk Management, and strong business acumen are assets.
• Strong communication skills (oral/written). Bilingual in English/French is an asset.

Responsibilities

• Design, build, and maintain highly scalable ELT/ETL data pipelines using modern cloud infrastructure (GCP, BigQuery, GCS). Architect processes to ingest, transform, and integrate large volumes of structured claims data and unstructured third-party data to build the foundational datasets required for advanced fraud analytics.
• Design, train, and iterate on predictive machine learning models and AI solutions. Focus heavily on Natural Language Processing (NLP) and Generative AI (e.g., prompt engineering with Gemini) to extract actionable fraud indicators from unstructured SIU data (case notes, medical records) and structured policy data.
• Conduct rigorous offline model evaluation (precision, recall, slice analysis). Champion Explainable AI (XAI) by utilizing methods like SHAP values or LLM reasoning traces to ensure model outputs are transparent, interpretable, and trusted by non-technical SIU investigators.
• Work closely with SIU stakeholders to understand emerging fraud schemes. Conduct in-depth EDA using SQL and Python to assess data feasibility and establish baseline metrics. Design and maintain internal automations and scheduled data retrievals to improve the operational efficiency of the analytics team.
• Draft comprehensive technical documentation detailing pipeline lineage, model architecture, and evaluation metrics. Promote software engineering best practices (version control, CI/CD) and work with compliance teams to ensure AI solutions adhere to data privacy standards (PII/PHI) and algorithmic fairness guidelines.

Benefits

• Hybrid work schedule for most roles
• Company share ownership program
• Incentive Program - Eligible employees may participate in various incentive plans which are paid out at the discretion of the company and subject to individual and company performance.
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior