Must include 2 years of experience in each of the following:Building scalable, production-grade analytical framework using Python large-scale distributed computing environments in Apache Spark and Hadoop/HIVE, SQL, Tableau, Alteryx including development of modular, reusable model components and automation of end-to-end data processing workflow;Developing and deploying financial forecasting models including implementation of monitoring routine, performance diagnostics, testing, and investigation of model outputs;Performing time-series analysis, multivariate regression, and econometric modeling on large financial datasets to identify structural, cyclical, and trend-based risk dynamics;Applying advanced statistical, econometric, and machine learning techniques to develop quantitative forecasting and risk measurement frameworks supporting enterprise-level portfolio and capital management processes; and,Integrating and analyzing diverse financial and alternative datasets-including market activity, firm level microeconomic indicators, sector performance metrics, consumer behavior trends, and macroeconomic variables-to support advanced quantitative risk assessment and concentration analysis. Analyze and evaluate large and complex economic and financial datasets using analytical tools such as Python, SQL, and R.Use big data technologies like SQL to handle large volumes of data produced by complex financial forecasting models.