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Credit Model Specialist

unlimited holidays - extra holidays - extra parental leave - long remote period allowed
Remote: 
Full Remote
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

Undergraduate degree in quantitative discipline, 5+ years credit risk model validation, Strong Python and R programming skills, Experience with SAS and/or Stata.

Key responsabilities:

  • Thorough model validation of credit decisioning
  • Evaluate predictive accuracy of model assumptions
  • Present work clearly to project lead

Job description

Overview:

Treliant is a global consulting firm serving banks, mortgage originators and servicers, FinTechs, and other companies providing financial services. We are led by practitioners from the industry and the regulatory community who bring deep domain knowledge to help our clients drive business change and address the most pressing compliance, regulatory, and operational challenges.

 

We provide data-driven, technology-enabled advisory, implementation, and staffing solutions to the regulatory compliance, risk, financial crimes, and capital markets functions of our clients.

 

Founded in 2005, Treliant is headquartered in Washington, DC, with offices in New York, London, Belfast, Northern Ireland and Łódź, Poland. For more information visit www.treliant.com.

 

Treliant is committed to fostering a diverse, equitable and inclusive environment that values and embraces all races, religions, ages, abilities, genders, sexual orientations, ethnicities, languages, nationalities, political parties, socioeconomic groups and other characteristics that inform an individual's worldview, experiences and system of beliefs (“the principles”). We believe in championing every voice and ensuring everyone’s full potential.

 

Treliant seeks Credit Risk Modelers for remote, project-based opportunities.  

 

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Primary Location: Remote

Primary Location Salary Range: $75/hr - $150/hr

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Responsibilities:
  • Perform thorough model validation of credit decisioning and related consumer lending models
  • Rigorously evaluate predictive accuracy of model assumptions against actual performance and requirements
  • Document results in a concisely written report
  • Clearly present work to the project lead
Qualifications:
  • Undergraduate degree in a quantitative discipline (i.e. statistics, econometrics, engineering)
  • Advanced degree a plus
  • 5+ years of credit risk model validation work experience within the financial services industry
  • Strong Python and R programming skills
  • Experience using SAS and/or Stata software packages a plus
  • Experience using Machine Learning packages and evaluating Machine Learning algorithms in consumer lending/leasing or similar businesses
  • Understanding of CCAR and DFAST 
  • Comfort working in a fast-paced and deadline-driven consulting environment
Benefits:

Upon eligibility, Treliant project-based employees can elect to participate in the firm’s health benefits and 401k matching plan.

 

If you want to be part of a dynamic team of professionals, we invite you to join the team at Treliant.  We invest in people, and challenge you to advance your career while achieving your aspirations and goals.  Here at Treliant, we pride ourselves on our collaborative team culture, where we embrace diversity of thought and innovation.  If you strive for excellence and seek an inclusive environment apply on line www.treliant.com and follow us on LinkedIn. 

 

 

 

Treliant LLC is an Equal Opportunity Employer and does not discriminate on the basis of race, color, national origin, sex, sexual orientation, genetic information, religion, age, disability, or military status in employment or provision of services. When contacted for an interview, an applicant who requires special accommodations due to a disability should notify the office so that proper arrangements can be made.

Required profile

Experience

Level of experience: Senior (5-10 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Verbal Communication Skills
  • Analytical Skills
  • Detail Oriented

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