Senior Data Analyst

Senior Data AnalystOur not-so-secret sauce.Award-winning, inclusive, Top Workplace culture doesn't happen overnight. It's a result of hard work by extraordinary people. More than 10,000 of the industry's brightest talent drive our efforts to deliver purposeful work and meaningful impact every day. Learn more about what makes us different and how you can thrive as a Platform Engineer at MMA.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).A day in the life.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.ResponsibilitiesAI-enabled analytics products. 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.QualificationsMaster'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 tuningPython for data processing and machine learningBuilding data pipelines on a cloud lakehouse platform such as Databricks, Microsoft Fabric or SnowflakeDimensional or tabular data modeling for BIDeveloping, evaluating or deploying machine learning or LLM-based solutionsStatistical analysis methodsDeep exposure to the FinTech with special focus on Insurance DomainStrong team player with ability to lead focus pods successfullyAbility to clearly articulate problem statements and design decisionsFlexible to pivot on feedbackFollow the agile disciplineValuable benefits.We value and respect the impact our colleagues make every day both inside and outside our organization. We've built a culture that promotes colleague well-being through robust benefit programs and resources, encourages professional and personal development, and celebrates opportunities to pursue the projects and causes that give colleagues fulfilment outside of work.Generous time off, including personal and volunteeringRemote workTuition reimbursement and professional development opportunitiesCharitable contribution match programsStock purchase opportunitiesThe applicable base salary range for this role is $100,000 to $150,000.The base pay offered will be determined on factors such as experience, skills, training, location, certifications, education, and any applicable minimum wage requirements. Decisions will be determined on a case-by-case basis. In addition to the base salary, this position may be eligible for performance-based incentives.We are excited to offer a competitive total rewards package which includes health and welfare benefits, tuition assistance, 401K savings and other retirement programs as well as employee assistance programs.