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AVP Machine Learning and Data Science (CRG 1751)
NPAworldwide Recruitment Network
NPAworldwide Recruitment Network
How to Apply:

Job Location: Las Vegas, NV

Job #: 38161
Title: AVP Machine Learning and Data Science (CRG 1751)
Job Location: Las Vegas, Nevada - United States
Employment Type:
Salary: $115,000.00 - $160,000.00 - US Dollars - Yearly
Other Compensation: Bonus 10-15%
Employer Will Recruit From: Nationwide
Relocation Paid?: Yes


This is a great bank with a super strong culture of accountability, analytics, and data. I`ve personally placed people at the level of a Senior Analyst and seen them advance up to C-level in under 10 years.

They have never laid off a person, not after 9/11, not in 2008, and not now. They don`t believe that a person should lose their job to improve the balance sheet. It doesn`t mean candidates are guaranteed a job forever. People who are not doing their job well will be released, but it will be after every effort is made to find a better fit within the organization.

There is ABSOLUTELY no flexibility on location, even in the midst of Covid-19. Relocation assistance is available. They will sponsor candidates who are already in the USA.

June 2021


Our client is a successful credit card issuing bank, headquartered in Las Vegas. Established more than 30 years ago, they are one of the largest and fastest growing banks in the industry, providing a broad spectrum of credit card products to over 7 million card members. They issue credit cards under their brand, as well as cobranded cards for the NHLs Vegas Golden Knights, NASCAR, and others.

This position is a part of the Risk Management department but supports the entire bank. The model development team challenges the status quo through their Machine Learning (ML) powered predictive models that covers the entire customer lifecycle including Acquisitions, Underwriting, Fraud, Customer Management and Collections. As the AVP of Decision Sciences and Machine Learning, you will lead the team in developing and enhancing custom models for portfolio risk, transaction fraud, attritions and collections with advanced data science skills; adopt applications of ML to enhance next generation solutions; and develop analytical tools with instrumental contribution to the strategic direction and financial performance of the organization.

Summary Essential Job Functions

  • Grows and leads a team of data scientists responsible for devising next generation modeling solutions for portfolio risk, transaction fraud, attritions and collections.
  • Designs and initiates extensive research on cutting edge ML algorithms including, but not limited to, Gradient Boosting, Random Forest, KNN to enhance the modeling solutions for the bank.
  • Leads the development of advanced analytic solutions and strategies through all aspects of the model development and implementation lifecycle.
  • Presentation of results and recommendations; particularly the ability to craft a coherent vision from complex output and data.
  • Serves as an in-house expert in the area of Machine Learning and Artificial Intelligence.
  • Undertakes initiatives to deploy ML algorithm to enhance existing and/or introduce new processes and show bottom line impact.
  • Partners with technology groups to define business requirements on Modeling and ML related projects.
  • Interacts with senior management and business owners.
  • Provides work direction to the data scientists & modelers and ensures accuracy and quality of their deliverables.
  • Anticipates issues based on knowledge of business trends and proposes direction and solutions.
  • Performs other duties as assigned.

  • Graduate degree in quantitative field such as statistics, mathematics, econometrics, engineering, computer science and equivalent industry experience.
  • 6+ years of experience in development and implementation of predictive models, ML solutions and data science; preferably within a financial services industry.
  • 1+ years of experience managing a team of analytical professionals.
  • Strong working knowledge of traditional algorithms such as Regression / Logistic Regression, Segmentation, Clustering and ML algorithms for predictive analytics such as Gradient Boosting, Random Forest, KNN etc.
  • Hands-on experience with statistical tools such as R, Python, SAS and database query languages (e.g., SQL).
  • Leadership skills to manage and mentor a team of analytical professionals across varying levels of skill and experience.
  • Solid planning, priority setting, and project management skills with experience managing multiple projects and resources concurrently.
  • Excellent written and oral communication skills, and the flexibility, and ability to thrive in a fast-paced, rapidly changing, highly complex environment.
  • Proven experience managing and delivering a wide variety of analytic solutions to stakeholders.
  • Self-starter who is highly motivated, collaborative, and innovative.
  • Demonstrate company core values of excellence, ownership, collaboration, and integrity.


  • Deeper understanding of the underlying logic of ML algorithms such as boosting, bagging, stacking etc.
  • Knowledge of credit card industry and key drivers of its revenue and losses.
  • Basic idea of second line model review, model governance and audit.

University - Master`s Degree

How to Apply:

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