Data Lake is the Firm’s strategic repository for enterprise data. Technology teams across the Firm are clients, participating in providing and consuming data to & from the lake. You will be part of the data lake machine learning and analytics team that leverages machine learning alongside big data engineering developers to continuously turn data into action.
Your role would be to apply machine learning and statistical techniques to predict, analyze and improve the performance of this highly complex big-data platform. You will be rapidly applying analytics/ML to predict trends of various components of the lake to drive strategical improvements of significant business value. You will also be designing these high impact models to run on big data and put them in production at scale.
You will be collaborating daily with big data developers in the lake to understand their requirements, and convert them into real-world applied ML/analytics problems to drive major business impact and cost savings. As part of understanding the problems of lake developers, you will work with latest technologies like Apache Spark, Flink, Elastic Search, HDFS, AWS to understand complex distributed applications which handle large data sets.
The Data Lake is being adopted by technology teams across the Firm at a very high rate. As a result, the platform is growing and evolving, and with it, its analytical/ML needs to monitor, predict and correct its behavior automatically from vast sources of data.
The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.
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