Data Analyst, Reinsurance Operations

Munich Re is the world’s leading reinsurance company with a commitment to innovation and diversity. As a Data Analyst in Reinsurance Operations, you will develop and optimize data workflows, ensure data integrity, and provide business insights through advanced analytics and collaboration with various teams.

Responsibilities

• Design, build, and maintain automated workflows using enterprise workflow tools to translate diverse client and treaty data streams—including billings, inforce, and claims into standardized formats for downstream processing
• Analyze data structures and business needs to create accurate mapping, transformation, and validation rules
• Collaborate with business partners to implement, test, and refine workflow solutions, ensuring they meet stakeholder needs and reporting standards
• Continuously monitor workflow performance, proactively identify bottlenecks, inefficiencies, or data quality issues, and recommend or implement improvements
• Document workflow processes, logic, and changes to support audit readiness and knowledge transfer
• Ingest, validate and transform large volumes of client, treaty, and claims data from multiple sources, applying rigorous quality control checks and reconciliations for accounts payable and receivables
• Conduct root cause analysis for failed validations and implement corrective actions
• Maintain and update mapping to internal treaty databases, ensuring accuracy, completeness, and consistency of key data fields
• Support the implementation of data quality rules and controls, tracking and resolving data-quality issues in collaboration with business and technical teams
• Build and enhance reports and dashboards for treaty performance, premiums, claims, lapses, profitability, and KPIs
• Design and optimize SQL queries and data models to support recurring reporting cycles and ad-hoc analysis requests
• Perform deep-dive analyses on trends, anomalies, and variances, presenting findings and actionable recommendations to stakeholders and leadership team
• Leverage advanced analytics and, where possible, AI-driven methods to uncover insights, automate data extraction, and support decision-making
• Partner with actuarial and claims teams to support experience studies, scenario analysis, and profitability reviews
• Support enhancements and implementations of reinsurance administration, data warehouse, and BI platforms, participating in requirements gathering, data mapping, testing, and user training
• Support data migration and reconciliation activities when onboarding new treaties, products, or systems
• Identify and recommend process improvements, automation opportunities, and best practices for data translation workflows and operational efficiency
• Stay current with emerging technologies, including AI/ML, and advocate for their adoption to drive innovation and continuous improvement
• Collaborate with actuarial, underwriting, claims, finance, legal, and IT teams to resolve data issues, clarify requirements, and deliver business objectives
• Act as a subject-matter resource on data for assigned clients and work with internal teams and external partners on operational implications stemming from format and/or treaty changes
• Translate complex analytics into clear, actionable messages for technical and non-technical audiences
• Prepare and deliver presentations, documentation, and updates for management and external partners
• Support internal and external audits by providing clear documentation of treaty terms, processes, and data flows
• Explore and, where appropriate, integrate AI/ML tools and techniques to supplement data ingestion, translation, and insight generation
• Experiment with large language models (LLMs) and AI-powered APIs to automate data extraction, translation, and reporting tasks
• Apply predictive analytics, anomaly detection, and automated reconciliation to improve outcomes

Skills

• Bachelor's degree in business, Finance, Actuarial Science, Data/Computer Science, Statistics, or related discipline
• Proficient with SQL and relational databases
• Strong Excel (pivot tables; Power Query/Power Pivot a plus)
• Experience with BI tools (Power BI, Tableau, etc.)
• Strong analytical skills; able to turn complex data into clear insights and recommendations
• Naturally curious—asks questions, digs deeper into trends, and seeks innovative solutions
• High attention to detail; disciplined approach to documentation, controls, and data quality
• Ability to connect contractual wording, operational processes, and data structures
• Clear communicator; collaborative, team-oriented mindset with ownership
• 1–2 years of experience in insurance/reinsurance data analysis, treaty administration, or reporting preferred
• Familiarity with reinsurance administration systems and/or data warehouse environments would be considered an asset
• Basic Python or R for analytics is a plus
• Exposure to AI/ML tools in a data context, such as:
• Using LLMs (large language models) to assist with data translation, document summarization, or insight generation
• Integrating AI services via APIs (e.g., anomaly detection, text extraction/classification) into data workflows
• Applying basic ML techniques (classification/regression/clustering) for operational or portfolio insights

Benefits

• An engaging and collaborative environment that promotes continuous learning and development
• A hybrid work environment that combines weekly in-office and remote days with Meeting-Free lunch hours and Focus Friday afternoons
• A great compensation package including annual company bonus
• Market leading company-paid flexible health and dental benefits, starting on your first day
• Flexible dollars provided by the company to put towards Health Spending Account and/or Wellness Spending Account
• Immediate participation in DC Pension Plan with an automatic 5% employer contribution, plus optional company match
• Generous time off including vacation, personal days, unplanned time, Statutory Holidays and company-wide early closure half-days
• Learning and development programs and resources, including unlimited access to LinkedIn Learning, Education Assistance Program and reimbursement for professional fees
• Maternity, Parental & Adoption Leave top-up program
• Employee Referral Program, Recognition & Rewards Platform

Company Overview