Analytics Scientist - Commercial Risk

US-MI-Detroit
Requisition ID
2017-30509
Employee Type
Full Time-Regular
Category
Risk Management / Insurance

Overview

Reporting to the Senior Manager of Advanced Analytics in Risk Management, the candidate will be responsible for Commercial portfolio risk analytics. The position requires the candidate to perform data management and analytics projects, support development of mathematical models to predict and measure the credit risk. In addition, he/she will have responsibilities related to the verification of dealer financial source information and the support of model validation.

Responsibilities

  • Take the initiative of data management, drive all phases of data preparation, support model development, and testing process to quantify risk
  • Analyze complex, large-scale datasets and utilize statistical methods including general linear model, logistic regression, cross-sectional and time series analyses, etc. to drive business decisions and outcomes
  • Document model methodology and testing process to meet model validation and audit requirements
  • Collaborate with internal modelling teams to set analytic objectives, approaches, and work plans
  • Achieve optimal analytic results by exploring various model building techniques, consulting relevant literature as necessary

Qualifications

  • Master’s degree in quantitative field such as Statistics, Economics, Mathematics, Operation Research, Quantitative Finance
  • Prior experience using R, SAS (Macro, SQL) with proficiency
  • Prior experience in data management and statistical model building is required
  • Prior credit risk related analytic role for financial service companies and/or the auto industry preferred

Skills and Knowledge

 

  • Demonstrated skills in large scale data manipulation and data mining
  • Strong programming skills in R and/or SAS are required.
  • SQL programming, Access, Excel skills are desirable
  • Demonstrated skills in conducting complex statistical analysis in a business or academic setting
  • Quick learner, high level of initiative, detail-oriented, and ability to multi-task.
  • Ability to translate advanced mathematical concepts into easily understood results for all levels of business customers
  • Good collaboration and communications skills (verbal and written)
  • Strong understanding of analysis and computational complexity and ability to programmatically solve problems
  • Excellent analytical mind-set, business results oriented, high on ethics, integrity

 

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