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Data Science Consultant

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Job Summary
Excellent opportunity in the Dallas area

We are looking for a passionate and highly-motivated Data Scientist with a background in Consumer Credit and Risk.

We are looking for a team player who will contribute to the success of your team, your department, and your company. The primary responsibility of this role is to uncover actionable insights from large sets of data, to provide advanced analytics and decision support for the company’s Consumer Credit business. You will design, develop, maintain, and improve models and strategies that have measurable impact on the lives of nearly 5 million consumers and the performance of our over $90 billion portfolio.


Job specs

  • Design, develop, refine and maintain company credit default models using statistical software and develop Risk scoring models based on credit bureau attributes and internal data.
  • Monitor performance of existing risk functionality (scorecards, forecasts, models, and strategies). Identify enhanced functionality and recommend improvements to leverage data science or analytics in credit risk management.
  • Refresh and use the advanced analytics models driving Company’s Collections Treatment Optimization program. Develop and manage forecasts using time series techniques, including ARIMA.
  • Assist in the computer implementation of models and strategies in our decision engine and other software environments, to support both batch and real-time decision support. Aid in the implementation of PD, LGD and EAD metrics for end-user accounts to better align communication of risk across the portfolio.
  • Collaborate across the Toyota enterprise and Communicate technical and business topics effectively with audiences ranging from IT and Risk Management specialists to executives.

Job requirements:

Detailed knowledge of advanced analytics modeling including several of

o    Descriptive analytics (univariate and multivariate statistics or data visualization)

o    Predictive analytics (supervised learning techniques such as logistic regression or Classification and Regression Trees (CART) or other tree-based techniques; and unsupervised learning models such as cluster analysis).

o    Time series forecasting techniques.

o    Prescriptive analytics: optimized decision strategies using methods such as decision tree models, linear programming, stochastic and/or dynamic modeling.

  • Experience in developing consumer credit scoring models or other credit loss models or strategies using credit reporting data. Experience implementing credit scorecards or other statistical models in production software.
  • An ability to communicate data-driven insights effectively with management and business stakeholders at their level of expertise and experience.
  • Knowledge of statistical software such as R, Python (Numpy/Pandas), or SAS.
  • Proficiency with SQL and data warehouses.
  • A Master’s degree in Statistics, Economics, Operations Research, Financial Engineering, or other math-related field. An advanced degree is preferred.

Find us at:

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Q-Lytics Consulting, Inc.
8352 Willow Run
Fogelsville, PA 18051
Phone: 610.530.1447

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