[Hiring] Senior Data Analyst @Marsh McLennan

Role Description

As a Senior Data Analyst, you will design, build and govern AI-enabled analytics products on the enterprise lakehouse and semantic layer, turning governed data into models, metrics and intelligent reporting used by business leaders. The role combines analytics engineering, machine learning and data architecture, applying computer science and statistical methods to build production analytics systems.

Responsibilities

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

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.

Benefits

• Generous time off, including personal and volunteering.
• Remote work.
• Tuition reimbursement and professional development opportunities.
• Charitable contribution match programs.
• Stock purchase opportunities.

Company Description

Marsh McLennan Agency (MMA) provides business insurance, employee health & benefits, retirement, and private client insurance solutions to organizations and individuals seeking limitless possibilities. With 180 offices across North America, we combine the personalized service model of a local consultant with the global resources of the world’s leading professional services firm, Marsh McLennan (NYSE: MMC).