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# Senior Data Analyst

- **Company:** Marsh
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $100,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Artificial Intelligence, Business Analytics Applications, Data Analysis, Business Intelligence Development, Information Systems, Information Engineering, Python (Programming Language), Machine Learning, Performance Tuning, Power BI, SQL Databases, Data Classification, Sql Optimization, Large Language Models, Snowflake, Build Management, Microsoft Fabric, Pyspark, Information Technology, Data Management, Data Pipelines, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/7_FEA3578144FE7C03FB8A71BC6EC59E96

## About the Role

Qualifications Master's degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Information Systems, Engineering or a closely related quantitative field,

or

a Bachelor's degree (or foreign equivalent) in one of those fields plus 5 years of progressive, post-baccalaureate experience in analytics engineering, data engineering, machine learning or BI development. Advanced SQL, including query performance tuning Python for data processing and machine learning Building data pipelines on a cloud lakehouse platform such as Databricks, Microsoft Fabric or Snowflake Dimensional or tabular data modeling for BI Developing, evaluating or deploying machine learning or LLM-based solutions Statistical analysis methods Deep exposure to the FinTech with special focus on Insurance Domain Strong team player with ability to lead focus pods successfully Ability to clearly articulate problem statements and design decisions Flexible to pivot on feedback Follow the agile discipline

## Description

Design and build analytics solutions that embed machine learning and large language models, including natural-language query over governed semantic models, automated insight generation, anomaly detection and forecasting on insurance and brokerage data. Analytics engineering on the lakehouse.

Build and optimize data models and transformation pipelines in Databricks and Microsoft Fabric using a medallion architecture, with SQL, Python and PySpark. Own data quality tests, lineage and performance tuning. Semantic layer and BI architecture.

Design tabular semantic models, DAX measures and row-level security for Power BI and Power BI Embedded, and support migration of legacy Analysis Services models. Model development and evaluation.

Apply statistical methods and ML techniques to select, train, validate and monitor models. Design evaluation frameworks for LLM outputs, including accuracy, grounding and bias checks. AI governance and security.

Implement controls so AI features respect data classification, access policies and row-level security. Partner with data management and AI strategy teams on responsible-AI standards. Stakeholder partnership.

Translate business questions from producers, finance and operations leaders into technical designs, and document solutions for offshore and vendor delivery teams.