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’s Regulatory Compliance and Risk Management practice is hiring a Statistician with a strong background in Fair Lending and related quantitative disciplines to join the team as an FTE.  This role is 100% remote.

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Primary Location: Remote

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

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• Develop customized logistic and ordinary least squares models and other statistical techniques to identify disparate impact on a prohibited basis in underwriting, pricing, credit line assignment, steering, or servicing loans.
• Perform thorough model validations of Fair Lending, Credit, and related models to the standards of SR 11-7.
• Develop and implement tests of algorithmic and data bias.
• Rigorously evaluate predictive accuracy of model assumptions against actual performance and requirements.
• Apply fair lending principles to test for discrimination in the provision of non-credit financial products and services.
• Document results and associated risks in concisely written reports.
• Clearly present work to both internal and external stakeholders.

• Undergraduate degree in a quantitative discipline (i.e. statistics, econometrics, engineering).
• Advanced degree a plus.
• 5+ years of Fair Lending, consumer credit, or related model development and validation work experience within the financial services industry.
• Strong SAS, Python and R programming skills.
• Experience using , RiskExec, Fair Lending Wiz, and 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 a plus.
• Comfort working in a fast-paced and deadline-driven consulting environment.

Treliant offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefit package that reflects our commitment to creating a diverse and supportive workplace.  In addition to a competitive base salary, candidate is eligible for incentive pay as well as a full range of health benefits, vacation plan, and 401k 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.