Information Technology•Contract•8+ years•Markham, Ontario•
Required Skills
7 skills
Snowflake
Hadoop
PostgreSQL
Informatica
Power BI
Tableau
Qlik
Job Description
<h3>Key Responsibilities</h3><ul><li>Claims & Policy Data Analysis: Analyze structured/semi-structured data on claims, policies, underwriting, and customer interactions. Detect patterns in claims frequency, fraud indicators, and loss ratios.</li><li>Customer & Risk Insights: Segment customers, assess risk profiles, and identify cross-sell/up-sell opportunities. Support compliance teams with risk monitoring.</li><li>Regulatory & Compliance Reporting: Prepare accurate data extracts for regulators (OSFI, FSRA, NAIC) and ensure lineage and traceability for audits.</li><li>Data Wrangling & Preparation: Clean and transform raw data from multiple systems using lakehouse tools such as Delta Lake or Apache Iceberg.</li><li>Business Intelligence & Visualization: Build dashboards with Power BI, Tableau, or Qlik and enable self-service analytics.</li><li>Data Quality & Governance: Profile data, catalog datasets with metadata tools (Unity Catalog, Collibra), and support master/reference data initiatives.</li><li>Collaboration & Stakeholder Engagement: Work closely with actuaries, underwriters, product managers, and IT to translate business questions into analytical models.</li><li>Advanced Analytics Support: Assist data scientists with feature engineering, data extracts for model training, and integration of model outputs.</li></ul>
Key Responsibilities
Claims & Policy Data Analysis: Analyze structured/semi-structured data on claims, policies, underwriting, and customer interactions. Detect patterns in claims frequency, fraud indicators, and loss ratios.
Customer & Risk Insights: Segment customers, assess risk profiles, and identify cross-sell/up-sell opportunities. Support compliance teams with risk monitoring.
Regulatory & Compliance Reporting: Prepare accurate data extracts for regulators (OSFI, FSRA, NAIC) and ensure lineage and traceability for audits.
Data Wrangling & Preparation: Clean and transform raw data from multiple systems using lakehouse tools such as Delta Lake or Apache Iceberg.
Business Intelligence & Visualization: Build dashboards with Power BI, Tableau, or Qlik and enable self-service analytics.
Data Quality & Governance: Profile data, catalog datasets with metadata tools (Unity Catalog, Collibra), and support master/reference data initiatives.
Collaboration & Stakeholder Engagement: Work closely with actuaries, underwriters, product managers, and IT to translate business questions into analytical models.
Advanced Analytics Support: Assist data scientists with feature engineering, data extracts for model training, and integration of model outputs.