Data Analyst
DATAECONOMY
Job Description
About Us
DATAECONOMY is one of the fastest-growing Data & Analytics companies with global presence. We are well-differentiated and known for our thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
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.
The Role
Data Analyst – Charlotte, NC (Full-time) – Insurance Domain
Responsibilities
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.
Requirements
- 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.
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.
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.
Benefits
Standard full-time benefits.
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