Bank of America Third Party Quantitative Operations Lead in Charlotte, North Carolina
Incumbent is responsible for developing quantitative/analytic models and applications in support of the firm's risk management effort. This role focuses on the development of operations/data management policies, strategies and operational guidelines for the organization's various financial products as they relate to the analysis, tracking, and reporting of various risk metrics. This role often possesses an advanced degree in physic, applied mathematics, statistics/probability or another heavy quantitative discipline. Quantitative analytic staff is focused on and responsible for the development of the theory and mathematics behind various models. May report to either Quant Operations Exec or Quantitative Operations Manager.
Responsible for driving business insight through the use of quantitative/analytical techniques in support of the firm's Global Procurement organization. The Quantitative Analyst will work with Global Procurement’s risk management, sourcing and strategy executives to drive significant business value through statistical analysis of Third Party behavior and risk. Key tasks may include:
Data Mining and gathering of structured / unstructured data across a wide infrastructure
Apply advanced analytical techniques to drive business insights and decisions
Conduct spend analytics to support the categorization of spend as well as to identify possible fraud in supply chain payment networks
Create a risk scoring model and build-out of inherent vs. residual risk framework for Third Party program
Create supply chain demand forecast and capacity models
Identify and quantify Third Party risk concentrations
Perform risk stress testing of Third Party portfolio
- 6-10 years experience in quantitative analysis and data mining through statistical techniques
-Bachelor’s Degree in a quantitative field plus Masters or PhD in progress
Ability to mentor and train junior quantitative analysts
Strong data manipulation skills using SQL
Strong knowledge of database management and related data structures
Strong knowledge of at least one quantitative programming language such as SAS, R or Python
Must be comfortable performing analysis in a dynamic environment with varying datasets and data quality
Strong communication and cross-group collaboration skills
Experience modeling operational losses or default probabilities
Experience analyzing unstructured data (e.g. text analytics)
Experience in Risk Management
Posting Date : 07/25/2017
Location : US-NC-Charlotte
Travel : Yes, 5% of the time
Full / Part-time : Full time
Hours Per Week : 40
Shift : 1st shift
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