Our Profession is our Passion! We atRangTechspecialize in planning, implementing, managing, and staffing InformationTechnology Solutionsand Services. Our goal is to help our clients define their investments in technology, optimize processes that bring fast-track success, and deliver business-critical applications to improve performance. We value diversity. We operate as one team, bringing highly qualified and experienced software and management professionals with advanced degrees in Computer Science, Management, Engineering, Statistics and Bioinformatics.
The values that drive our success are:
Strategy:Wehelpour clients growth by achieving competitive advantage and creating value.
Quality:We believe in Quality First and Quality Must in solutions we deliver.
Support:We bring ideas and talent to empowerbusiness performancewith new-age technologies.
We take pride inbuildingstrategiclong-term relationship with our clients.
- Develop and validate Credit Risk models in different industries.
- Research the frame work of credit risk models
- Collect data for Credit risk modeling
- Prepare Data for modeling
- Using R , SAS or PYTHON, Weka for model building and model validation
- Document the process present the finding to the management
- Prepare PowerPoint presentations and document preparation for the entire credit risk modeling process.
- Collaborate, Support, Advise and Guide in development of the models.
- MS in Finance, Financial Engineering, Analytics or Mathematics, Computer Science, Statistics, Industrial Engineering, Operations research, or related field.
- Good understanding of Probability of Default (PD), LGD and EAD modeling technique.
- Very good understanding of Predictive modeling techniques and their application.
- Knowledge of Credit life cycle.
- Statistics and machine learning techniques.
- Conducted and applied statistical methodologies including linear regression, logistic regression, ANOVA/ANCOVA, CHAID/CART, cluster analysis
- Team player and collaboration skills.
- Programming skills in R, SAS, and PYTHON.
- Fluency with Excel, PowerPoint and Word
- Strong written and oral presentation / communication skills must have the ability to convey complex information simply and clearly
Nice to have:
- Relevant experience in banking/capital markets at a commercial bank with a well-developed credit risk management infrastructure or comparable experience working as an advisor to a financial services company
- Demonstrated knowledge in credit and/or market risk measurement and management
- Experience at a regulatory or rating agency in the areas of credit risk management, risk rating systems, regulatory capital, and/or capital markets
- Thorough understanding of some or all of the following:
- Credit lifecycle within a commercial bank
- Credit risk management infrastructures
- Good quantitative methods and tools supporting credit risk measurement
- Current industry and regulatory issues (Basel II)
All your information will be kept confidential according to EEO guidelines.