Risk - Business Banking Core Modeler - VP
Plano, TX, USA | J.P. Morgan
Functions:Financial Services Professional
Job Description:121 people have viewed this job
The CCB Risk Core Modeling Statistician will be responsible for end-to-end management of complex model development and ad-hoc analytic projects to drive innovation and research new opportunities for revenue growth or risk mitigation. Success in this role requires a strong foundation in predictive modeling and machine learning coupled with experience in working with large dataset.In this highly visible role, the successful candidate will be able to think like an analytic leader with strong business acumen, collaborate in a team environment and communicate the business analytics and model statistics/insights succinctly to senior management.
The incumbent will need to work well in a matrix environment, working directly with Model Reviewers and business partners.
Your key responsibilities will include:
Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to discover useful information.
Analyze and interpret big data and its impact in both operational and financial areas following comprehensive risk principles and procedures.
Feature engineering and feature selection for traditional GLM models and machine learning models
Design, develop, implement and validate statistical models and segmentation strategies for the bank’s risk scoring, marketing, collection, and /or Comprehensive Capital Analysis and Review processes, as needed. Utilize graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using logistic regression, multinomial regression, multivariate analysis, discriminant analysis, neural network, principal components analysis, time series analysis, panel data analysis and etc.
Conduct complex risk analysis to provide management with business insights, recommendations of strategies and business actions for profitable growth opportunities, consumer credit quality and behavior trends, desired risk/return relationships and portfolio performance.
Partner with business units in making strategic choices and investment decisions. Communicate opportunities, financial and process trade-offs from advanced statistical methods to senior leaders.
Minimum of 5years of hands on work and research experience of advanced analytical skills in the areas of statistical modeling and data mining
Master's degree in Mathematics, Statistics, Computer Science, or related fields
Expert in generalized linear models, unsupervised and supervised machine learning algorithms
Demonstrated experience with Big Data tools like Hadoop & Spark
Demonstrated proficiency in advanced analytical languages such as R, Python, Scala, SAS
Experience with traditional database/system languages (e.g. SAS, SQL, etc.) to collaborate with other data analysts/systems
Ph.D.or MS in Mathematics, Statistics, Computer Science, or related field
Prior experience of data analytics and model development in financial Industry