Data Scientist

The Data Scientist will work closely with Chief Risk Officer and other senior executives in order to develop and execute on a modeling strategy and architecture to support various client’s customer acquisition channels including online, branch and partner channels.

Job Responsibilities:

  • Uses advanced modeling and statistical techniques, and tools such as SAS and R, develop and maintain credit risk, pricing, and fraud models and analytical strategies that will optimize lending decisions across channels
  • Conducts evaluation of new statistical approaches and enhanced segmentation to optimize approval and advance assignment strategies
  • Studies new data sources for additional lift to credit decisions; provides recommendations as to cost/benefit analyses of new data sources
  • Designs tests and champion/challenger strategies to continuously evaluate new opportunities to improve volume/credit risk trade-offs
  • Supports the business by conducting ad-hoc portfolio analyses and developing recommendations aimed and improving portfolio credit performance and profitability
  • Maintains up-to-date inventory and chronology of scores and underwriting strategies
  • Updates executive team on the impact of new scores and strategies on the company’s performance
  • Evaluates, recommends, and champions new modeling tools, techniques, and approaches
  • Represents Risk department in cross-functional projects and partner across the organization to execute on key business priorities

Skills & Qualifications:

  • Bachelor’s degree in a quantitative field of study (statistics, mathematics, economics, engineering, etc.) with strong academic record. Master’s degree preferred.
  • Three (3) to seven (7) years of experience developing models in R, Python or SAS required
  • Advanced abilities to handle large datasets; SQL programming experience is a big plus
  • Experience in financial services is preferred but not required
  • Power user of Excel (pivots, advance formulas, macros)
  • Self-starter with exceptional work ethic, motivation and desire to learn
  • Results oriented individual with the ability to translate plans into actions.
  • Superior attention to detail and organizational skills.

Job Location:

Baltimore, MD

Job Description:

The Data Scientist will work closely with Chief Risk Officer and other senior executives in order to develop and execute on a modeling strategy and architecture to support various client’s customer acquisition channels including online, branch and partner channels. Job Responsibilities:
  • Uses advanced modeling and statistical techniques, and tools such as SAS and R, develop and maintain credit risk, pricing, and fraud models and analytical strategies that will optimize lending decisions across channels
  • Conducts evaluation of new statistical approaches and enhanced segmentation to optimize approval and advance assignment strategies
  • Studies new data sources for additional lift to credit decisions; provides recommendations as to cost/benefit analyses of new data sources
  • Designs tests and champion/challenger strategies to continuously evaluate new opportunities to improve volume/credit risk trade-offs
  • Supports the business by conducting ad-hoc portfolio analyses and developing recommendations aimed and improving portfolio credit performance and profitability
  • Maintains up-to-date inventory and chronology of scores and underwriting strategies
  • Updates executive team on the impact of new scores and strategies on the company’s performance
  • Evaluates, recommends, and champions new modeling tools, techniques, and approaches
  • Represents Risk department in cross-functional projects and partner across the organization to execute on key business priorities
Skills & Qualifications:
  • Bachelor’s degree in a quantitative field of study (statistics, mathematics, economics, engineering, etc.) with strong academic record. Master’s degree preferred.
  • Three (3) to seven (7) years of experience developing models in R, Python or SAS required
  • Advanced abilities to handle large datasets; SQL programming experience is a big plus
  • Experience in financial services is preferred but not required
  • Power user of Excel (pivots, advance formulas, macros)
  • Self-starter with exceptional work ethic, motivation and desire to learn
  • Results oriented individual with the ability to translate plans into actions.
  • Superior attention to detail and organizational skills.

Job Qualifications:

The Data Scientist will work closely with Chief Risk Officer and other senior executives in order to develop and execute on a modeling strategy and architecture to support various client’s customer acquisition channels including online, branch and partner channels.

Job Responsibilities:

  • Uses advanced modeling and statistical techniques, and tools such as SAS and R, develop and maintain credit risk, pricing, and fraud models and analytical strategies that will optimize lending decisions across channels
  • Conducts evaluation of new statistical approaches and enhanced segmentation to optimize approval and advance assignment strategies
  • Studies new data sources for additional lift to credit decisions; provides recommendations as to cost/benefit analyses of new data sources
  • Designs tests and champion/challenger strategies to continuously evaluate new opportunities to improve volume/credit risk trade-offs
  • Supports the business by conducting ad-hoc portfolio analyses and developing recommendations aimed and improving portfolio credit performance and profitability
  • Maintains up-to-date inventory and chronology of scores and underwriting strategies
  • Updates executive team on the impact of new scores and strategies on the company’s performance
  • Evaluates, recommends, and champions new modeling tools, techniques, and approaches
  • Represents Risk department in cross-functional projects and partner across the organization to execute on key business priorities

Skills & Qualifications:

  • Bachelor’s degree in a quantitative field of study (statistics, mathematics, economics, engineering, etc.) with strong academic record. Master’s degree preferred.
  • Three (3) to seven (7) years of experience developing models in R, Python or SAS required
  • Advanced abilities to handle large datasets; SQL programming experience is a big plus
  • Experience in financial services is preferred but not required
  • Power user of Excel (pivots, advance formulas, macros)
  • Self-starter with exceptional work ethic, motivation and desire to learn
  • Results oriented individual with the ability to translate plans into actions.
  • Superior attention to detail and organizational skills.
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