About the role
Note: Candidate needs to be onsite Mon/Tue/Wed (this is mandatory) First round will be Virtual and 2nd customer round will be in-person.
About the Role and Job: Job Title: Data System Analyst Location: Markham, ON Model: Hybrid (3 Days Onsite (Mon/ Tues/ Wed)) Job Type: Full time
What you’ll do
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
Similar Jobs
About the role
Note: Candidate needs to be onsite Mon/Tue/Wed (this is mandatory) First round will be Virtual and 2nd customer round will be in-person.
About the Role and Job: Job Title: Data System Analyst Location: Markham, ON Model: Hybrid (3 Days Onsite (Mon/ Tues/ Wed)) Job Type: Full time
What you’ll do
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.