Data Analyst

We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.

Analytics & Reporting

• Turn business questions from underwriting, claims, actuarial, and finance teams into well-structured analyses and repeatable reports.
  
• Build and maintain dashboards and scorecards for KPIs such as loss ratio, combined ratio, premium growth, retention/lapse, and claims cycle time.
  
• Perform exploratory analysis to surface trends, anomalies, and opportunities (e.g., emerging loss patterns, fraud indicators, leakage).
  
• Document assumptions, definitions, and methodology so results are transparent and auditable.
  

Insurance Domain Analytics

• Analyze policy, premium, claims, and billing data to support pricing, reserving, and portfolio management discussions.
  
• Support loss-ratio, frequency/severity, and retention/churn analyses for P&C and/or L&A lines of business.
  
• Partner with actuarial and underwriting teams to validate data and interpret results in business context.
  

Data Preparation & SQL

• Write and optimize SQL to extract, join, and aggregate data from the lakehouse / data warehouse.
  
• Profile, clean, and validate datasets; flag and help resolve data quality issues with engineering.
  
• Build reusable, well-documented queries, views, and semantic-layer definitions.
  

Visualization & Stakeholder Enablement

• Design clear, decision-oriented visualizations in Power BI / Tableau (or equivalent).
  
• Translate analysis into concise narratives and recommendations for non-technical business stakeholders.
  
• Enable self-service by documenting metrics and curating trusted data sources.
  

Technology Stack

• Strong SQL across cloud data warehouse / lakehouse environments (Databricks SQL, Snowflake, BigQuery, or similar).
  
• BI/visualization tools  Power BI and/or Tableau.
  
• Spreadsheet modeling (Excel) for ad-hoc analysis.
  
• Working knowledge of Python (pandas) for data wrangling is a plus.
  

Required Qualifications

• 4–7+ years of experience in data analysis, business intelligence, or reporting.
  
• Strong, demonstrable SQL skills (complex joins, window functions, aggregations, query tuning).
  
• Proven experience building dashboards and reports in Power BI and/or Tableau.
  
• Solid understanding of data modeling concepts (dimensional / star schema) from a consumer's perspective.
  
• Ability to translate ambiguous business questions into structured analysis and clear deliverables.
  
• Strong written and verbal communication with business stakeholders.
  

Preferred Skills

• Insurance domain knowledge P&C and/or Life & Annuities; familiarity with premium, claims, and loss-ratio concepts.
  
• Experience with cloud data platforms (Databricks, Snowflake, Azure/AWS/GCP).
  
• Python (pandas) or R for analysis and automation.
  
• Statistical analysis fundamentals and A/B or cohort analysis experience.
  
• Exposure to data governance, metadata, and trusted-source / semantic-layer practices.
  
• Awareness of PII/PHI handling and regulated-data sensitivity.
  

Requirements

• Strong SQL complex joins, window functions, aggregation, query tuning
  
• Power BI and/or Tableau dashboard and report development
  
• Data modeling literacy dimensional / star schema (consumer perspective)
  
• Ability to translate business questions into structured analysis
  
• Strong stakeholder communication and storytelling
  
• 4–7+ years in data analysis / BI / reporting
  

Benefits