Software Engineering - Spark Developer
JP Morgan Chase Hyderabad, Telangana

Address: Building No. 11, Raheja Mindspace, Building 20 K.Raheja I.T. Park, Hitech City Road, Vittal Rao Nagar, HITEC City, Hyderabad, Telangana 500081

Hours: 

Open ⋅ Closes 9PM

Phone: 040 6724 0000

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.6 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at http://www.jpmorganchase.com/. The Corporate Technology (CT) organization develops applications and provides technology support for corporate functions across JPMorgan Chase, including Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and all functions within the Corporate Administrative Office (CAO). The RQD (Risk Quantitative Development) IT Organization has responsibility for implementation of Retail financial models in credit, collections, fraud, and regulatory reporting, as well as providing firm-wide model governance systems, and analytical environments for business analysts and model developers. The Risk Quantitative Development (RQD) Model Implementation team helps modelers implement their models into production. Our activities include perform development, enhance and support the code in Python so that it can be implemented as per regulatory guidelines. This team is also responsible for validating output of models with modeling team before it can be implemented in production environment. Other functionalities include creating reports like PROC Means, PSI, Characteristic Report and various other control reports in conjunction with reporting and modeling team. As part of Current regulatory guidelines, financial institutions need to comply with Allowance Allocation (provisioning) based on expected credit loss. Hence financial institutions are working on developing a Forward-Looking lifetime credit loss estimation model. Leveraging on the latest technology platform and an opportunity to build the most granular level model, this initiative of developing/implementing model will be used to forecast cash flows, credit losses and recoveries, Pre-Provision Net Revenue, and balance sheet projections for the purposes of the Comprehensive Capital Analysis and Reviews. The Risk Quant Developer will be a hands-on technical member of the Model Implementation team, and will work closely with the Modeling team, Data Management and Orchestration team to implement models in production. The candidate must be a talented programmer with the skills listed below and a pro-active problem solver. In addition, the candidate must exhibit a thorough understanding of model implementation, data structures, data manipulation, distributed processing, application development, and automation. The candidate must have a solid understanding of consumer financial products, data systems and data environments, and processes that are necessary for the implementation of Risk and Finance models.Responsibilities: The Risk Quant Developer will be a member of the teams that designs and develops robust automated solutions in partnership with Model Design teams and other stake-holder groups in Risk and Finance. The ideal candidate will possess strong technical skills and an understanding of data systems, and will execute the end-to-end implementation effort. Develop, test, and maintain data and analytics needed for risk and finance models Process analysis and process improvement, Create and maintain technical documentation, Contribute to the group’s knowledge base by finding new and valuable ways to approach problems and projects. Deliver high-quality results under tight deadlines Experience manipulating and summarizing large quantities of data. Knowledge of the consumer lending lifecycle, including loan origination, sale/servicing, default management/loss mitigation Qualifications Degree in computer science or a numerate subject (e.g. engineering, sciences, or mathematics) or Bachelor's degree with 6 years of experience, or Master’s degree with 4 years of experience, or a Ph.D. and two years of experience. Development and implementation experience of applications for 5-7 years. 2 to 4 years’ experience designing and developing in Python. Strong Knowledge and experience on Spark Strong experience in Hadoop Platform (Hive, HDFS and Spark) Hands on Working experience with Unix shell scripting experience with SQL, Oracle, Teradata etc is required good experience with Spark Software Knowledge of Java and Scala Preferred Qualifications: 5 years' experience with version control tools and processes (Subversion, CVS, Clear Case etc. 3 years' experience in programming additional languages, especially C++, R, SAS