Vice President, Data Analytics

Job description

Lead a team of data and business analysts to provide complex data analytical support for Chase Mortgage Banking Loss Forecast team on implementing, calibrating, and monitoring of loss forecast models. Provide support for mortgage loss forecast numbers in company's financial statements, risk appetite, ICAAP and CCAR. Provide exploratory data support on ad-hoc mortgage bank requests focused on losses, loan characteristics and borrower behavior. Provide support on portfolio risk management and various data analysis work for teams across Accounting, Finance, and other cross-functional risk teams within the Consumer & Community Banking line of business within JPMC. Utilizes graduate-level research and analysis skills. Manage a team of 5 people.

Desired profile

Education: PhD degree in Mathematics, Statistics or related quantitative field

Experience: 2 years of work experience in job offered or in a statistician-related occupation

Special skills: Position requires:

1. 2 years of experience in SAS programming, including experience in large-scale data
cleansing, manipulation, big data reporting and visualization, Business Intelligence development and Quality Control experience, and meta-programming and optimization;
2. 2 years of experience in SQL, including reporting in SQL;
3. 2 years of working experience with Oracle DB2, Teradata SQL platforms;
4. 2 years of industrial working experience with high-dimensional data and large-scale mining projects;
5. 2 years of experience extracting core analytic results from a noisy data environment, to detect and quantify underlying anomalies behind huge amount of information;
6. 2 years of experimental design experience to provide big data solutions with practical and feasible time/space/resource cost;
7. 2 years of experience with thorough theoretical and applied understanding in prediction models, including generalized linear models, MCMC, pattern recognition, non-parametric classification, probabilistic models; and,
8. 2 years of experience understanding, illustrating, and calibrating PD/LGD/EAD model
forecasting results.