Position: Data Analyst Location: Gurgaon Timings: 12:00 PM to 10:00 PM Role Overview: Doing independent research, analyze, and present data as assigned Expected to work in close collaboration with the EXL team and clients on Commercial insurance actuarial projects for US/UK markets Should be able to understand risk and underwriting , plicate rating methodology Develop and use collaborative relationship to facilitate the accomplishment of working goals Working experience in P&C insurance domain for US insurance markets is a must Excellent written and verbal communication skills Facilitate data requirements while working with actuaries Have excellent SQL skills to extract data for scheduled processes and adhoc requests Automate manual processes and ETL pipelines using Python Utilise/help migrate existing SAS processes from SAS to SAS Viya Key Responsibilities: Collaborate with actuaries to understand their data and reporting needs related to premium, loss, and exporsure analysis. Build and optimize complex SQL queries to extract, join, and aggregate large datasets from multiple relational sources. Develop and automate data pipelines in Python for ETL ,data wrangling , and wexploratory analytics. Use SAS for legacy processes, statistical outputs, and ad hoc data manipulation as required by actuarial models/processes Validate data outputs for accuracy and consistency, troubleshoot discrepancies, and ensure data quality before delivery Create documentation of data logc, process flows, and metadata over confluence and SharePoint to ensure transparency and knowledge sharing. Contribute to continuous improvement by recommending process automation or optimization opportunities in existing workflows Support Dashboarding or visualization needs(optional) using tools like Powe BI. Work in an agile or iterative environment with clear communication or progress, blockers and timelines. Required Skillset: SQL(Expert Level) : Complex Joins, subqueries, window functions, CTEs, query Optimization and performance tuning, working with large tables in cloud/on-premise environments( Teradata, SQL Server, or equivalent) Python( intermediate to expert): Data wrangling using pandas, NumPy, Script automation and API Consumption, Familiarity with Visual Studio, Jupyter and modular Python Scripting SAS(Intermediate): Reading/ writing from/to datasets, connecting with external sources, macros, PROC SQL Knowledge of AWS is preferred Experience with commercial insurance Understanding of actuarial concepts such as loss triangles, reserving, and pricing Exposure to Git, JIRA, Confluence Proficiency in Excel, VBA Macros(Preferred) Candidate Profile: Bachelor’s/Master's degree in engineering, economics, mathematics, actuarial sciences, or similar technical degree. Master’s in business or financial management is also suitable Affiliation to IAI or IFOA, with at least 3 actuarial exams 3-8 years’ experience in data analytics in insurance or financial service industry with good understanding of actuarial concepts - pricing, reserving, and/or valuation Demonstrated ability to work with actuarial or statistical teams in delivering high-quality data and insights Strong problem solving attitude and comfort with ambiguity in requirements Strong ability to learn technical and business knowledge Outstanding written and verbal communication skills Excellent time and work management skills Able to work in fast pace continuously evolving environment and ready to take up uphill challenges Is able to understand cross cultural differences and can work with clients across the globe
