Jogesh Gurjar

Software Engineer

Noida, Uttar Pradesh, India0 mo experience

Key Highlights

Architected high-throughput systems for loan processing.
Improved product flexibility by 90% through payment functionality.
Optimized UI rendering time by 80% for large datasets.

Stackforce AI infers this person is a Backend Developer in Fintech, specializing in high-performance systems.

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Skills

Core Skills

JavaSpring BootRestful Api Development

Other Skills

Agile MethodologiesAlgorithmsC++CI/CD PipelinesCredit Risk Modeling ToolsData ArchitectureData StructuresDatabase Management System (DBMS)Database OptimizationDatabase Query OptimizationDocker ProductsGitGitlabHibernate/JPAJUnit

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Nucleus software

Software Engineer

Jul 2023 – Present · 2 yrs 10 mos · Noida, Uttar Pradesh, India · On-site

Architected high-throughput concurrent processing system handling 100,000+ loan applications simultaneously using advanced multithreading and multi-node clustering, resulting in 300% improvement in processing capacity.
Developed comprehensive payment generation functionality for co-applicant workflows through UI, RESTful APIs, and SOAP integration, increasing product flexibility and user adoption by 90%
Optimized critical UI components reducing rendering time by 80% and improving select/deselect functionality by 90% for large datasets through strategic architectural redesign
Enhanced performance of major upload processes across the platform while implementing robust debugging and troubleshooting protocols to maintain 99.5% system stability
Collaborated with cross-functional teams to deliver enterprise-grade solutions using Java, Spring Boot, and Hibernate technologies in agile development environment

JavaSpring BootHibernate/JPARESTful API DevelopmentSOAPMultithreading+1

Axis bank

Buisness Analyst

May 2022 – Jul 2022 · 2 mos · Bengaluru, Karnataka, India · On-site

Analyzed credit risk model performance by studying monitoring matrices for stability and performance validation of credit scorecards using statistical analysis techniques.
Performed comprehensive data analysis using SAS Enterprise Guide tool to identify trends and insights for risk assessment improvement.
Revamped Model Monitoring Framework on SAS Viya platform implementing new data architecture patterns and improving backend-to-frontend data presentation by 40%.
Created detailed SAS Viya reports for multiple Application Scorecards enabling data-driven decision making for credit risk management teams.

SAS ViyaSAS Enterprise GuideStatistical Analysis