Job description
Department: OPERATIONS
Division: OPERATIONS
JOB PURPOSE:
Acts as an advisor to the business and helps relate and interpret the analyses to identify specific business issues, solutions and competitive advantage.
Lead advancement in best practices in relation to the collection, analysis, visualization, and communication of decision based metrics to improve products and to optimize operational and financial performance.
DUTIES AND RESPONSIBILITY:
Leads the design and build of cutting edge risk and pricing models to optimize our lending decisions by using advanced modeling and simulation techniques to optimize the performance of our loan products and operations
Leads and/or participates in the design of state-of-the-art software tools to collect, process, and analyze large volumes of structured and/or unstructured data that are often sparsely populated and prone to data inaccuracies.
Apply statistical analysis and predictive modeling to help our marketing teams acquire and retain more valuable customers
Investigate new analytics methodologies, use cases, and data sources, to institute new and best practices within the department.
Use advanced data mining techniques to identify and fight fraud.
Use pattern matching and algorithms to develop insights into the organization’s IT operations, predicting service incidents or impending resource shortfall
Analyze the trade-off between different levers across the product lifecycle (pricing, volume etc.), how this relationship impacts overall cash flow, revenue and financial/portfolio strategies and to provide recommendations on how to improve product performance.
QUALIFICATIONS:
Advanced degree in actuarial science, mathematics, statistics, economics, or applied sciences.
10+ years of quantitative experience in an advanced analytics, financial engineering, risk analytics or related role required.
KEY SKILLS REQUIRED:
Strong background in machine learning, hypothesis testing, regression analysis, statistics, or probability, as well as experience creating predictive analytics on high dimensional, noisy data that may also contain missing values preferred.
Experience working with large volumes of data composed of different instruments, coming from different sources.
Experience in natural language processing, especially in text analytics and news aggregation methodologies preferred.
Hands-on technical experience with conceptualizing large scale data solutions, such as — Hadoop, Teradata, Sybase IQ, Microsoft Analytics Platform System (Client), etc. preferred.
Knowledge of statistics, machine learning and predictive modeling
Experience with statistical software packages (such as SAS, R), and/or applications for data visualization and reporting to end users (such as Business Objects, Qlik or Tableau)
A deep and broad understanding of core and emerging analytics methods and approaches and how they can be deployed to drive value within and across client organization.
WORK CONDITIONS
On-call availability
Willingness and ability to travel and be away for long periods of time at a go
