Job Title: Data System Analyst
Location: Markham, ON Model: Hybrid (3 Days Onsite (Mon/ Tues/ Wed)) Job Type: Full time CAD120K
What you’ll do
1. Claims & Policy Data Analysis* Analyze structured and semi-structured data related to claims, policies, underwriting, and customer interactions.
- Identify patterns in claims frequency, fraud indicators, and loss ratios using lakehouse datasets.
- Support actuarial teams with data extracts and trend analysis.
2. Customer & Risk Insights* Segment customers based on behavior, risk profiles, and product usage.
- Analyze customer lifetime value, churn risk, and cross-sell/up-sell opportunities.
- Collaborate with risk and compliance teams to monitor exposure and regulatory thresholds.
3. Regulatory & Compliance Reporting* Prepare data extracts and reports for regulatory bodies (e.g., OSFI, FSRA, NAIC).
- Ensure data lineage and traceability for audit and compliance purposes.
- Validate data accuracy and completeness for filings and disclosures.
4. Data Wrangling & Preparation* Clean and transform raw data from diverse sources (e.g., policy admin systems, CRM, claims systems) into analytics-ready formats.
- Leverage lakehouse tools (e.g., Delta Lake, Apache Iceberg) to manage versioned and time-travel datasets.
- Collaborate with data engineers to ensure efficient ETL/ELT processes.
5. Business Intelligence & Visualization* Build dashboards and visualizations for underwriting, claims, finance, and product teams.
- Use tools like Power BI, Tableau, or Qlik to present insights from lakehouse data.
- Enable self-service analytics by creating reusable datasets and semantic layers.
6. Data Quality & Governance* Profile and validate data to ensure consistency across policy, claims, and financial domains.
- Tag and catalog datasets using metadata tools (e.g., Unity Catalog, Collibra).
- Support master data management and reference data initiatives.
7. Collaboration & Stakeholder Engagement* Work with actuaries, underwriters, product managers, and IT teams to understand data needs.
- Translate business questions into analytical queries and data models.
- Document business logic, assumptions, and data definitions clearly.
8. Predictive & Advanced Analytics Support* Assist data scientists with feature engineering and exploratory data analysis.
- Provide historical data extracts for model training and validation.
- Interpret model outputs and integrate them into business reporting.
What you’ll bring University degree in Computer Engineering or Computer Science.
- Minimum 5 years’ of experience successfully leading Data Systems Analysis organizations with expertise in building large-scale enterprise data assets.
- 8+ years’ experience as a Business Analyst working on mid-large projects for data design, development, and implementation of business-critical enterprise data systems.
- Solid grasp/experience with data technologies & tools (Snowflake, Hadoop, PostgreSQL, Informatica, etc.,)
- Outstanding knowledge and experience in ETL with Informatica product suite.
- Experience establishing documentation standards frameworks for data quality, data governance, stewardship and metadata management.
- Ability to foundationally understand complex business process driving technical systems.
- Strong leadership and influencing skills at the senior management level.
- Strong analytical, critical thinking and problem-solving skills.
- Strong stakeholder management.
- Solid understanding of Project and Program Management processes.
- Excellent verbal and written communication skills.
- Insurance knowledge an asset
Requirements
Job Title: Data System Analyst
Location: Markham, ON Model: Hybrid (3 Days Onsite (Mon/ Tues/ Wed)) Job Type: Full time CAD120K
What you’ll do
1. Claims & Policy Data Analysis* Analyze structured and semi-structured data related to claims, policies, underwriting, and customer interactions.
- Identify patterns in claims frequency, fraud indicators, and loss ratios using lakehouse datasets.
- Support actuarial teams with data extracts and trend analysis.
2. Customer & Risk Insights* Segment customers based on behavior, risk profiles, and product usage.
- Analyze customer lifetime value, churn risk, and cross-sell/up-sell opportunities.
- Collaborate with risk and compliance teams to monitor exposure and regulatory thresholds.
3. Regulatory & Compliance Reporting* Prepare data extracts and reports for regulatory bodies (e.g., OSFI, FSRA, NAIC).
- Ensure data lineage and traceability for audit and compliance purposes.
- Validate data accuracy and completeness for filings and disclosures.
4. Data Wrangling & Preparation* Clean and transform raw data from diverse sources (e.g., policy admin systems, CRM, claims systems) into analytics-ready formats.
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