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Credit Risk Data Science Jobs in Utah (NOW HIRING)

First Electronic Bank

CECL Analyst

Salt Lake City, UT · On-site

The ideal candidate has strong analytical skills, attention to detail, and a desire to grow within credit risk and financial modeling. What You'll Do: * CECL Data & Modeling Support * Assist with ...

First Electronic Bank

CECL Analyst

Salt Lake City, UT · On-site

The ideal candidate has strong analytical skills, attention to detail, and a desire to grow within credit risk and financial modeling. What You'll Do: * CECL Data & Modeling Support * Assist with ...

First Electronic Bank

CECL Analyst

Salt Lake City, UT · On-site

The ideal candidate has strong analytical skills, attention to detail, and a desire to grow within credit risk and financial modeling. What You'll Do: * CECL Data & Modeling Support * Assist with ...

Tendo

Principal Data Scientist

Salt Lake City, UT · On-site +1

$131.75K - $178.25K/yr

The Principal Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and ...

Tendo

Principal Data Scientist

Salt Lake City, UT

$131.75K - $178.25K/yr

The Principal Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and ...

Tendo

Senior Data Scientist

Salt Lake City, UT · On-site

$110.50K - $149.50K/yr

The Senior Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and private ...

MasterCard

Senior Data Scientist

Holladay, UT · On-site

Role As an individual contributor working within a growing data science team, you will take ... Focused in the first instance on affordability/credit decisioning and identity/income verification ...

Tendo

Senior Data Scientist

Salt Lake City, UT · On-site +1

$110.50K - $149.50K/yr

The Senior Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and private ...

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Credit Risk Data Science information

What are the key skills and qualifications needed to thrive as a Credit Risk Data Scientist, and why are they important?

To thrive as a Credit Risk Data Scientist, you need strong analytical skills, proficiency in statistical modeling, and a solid background in finance, mathematics, or a related field, often supported by an advanced degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of credit risk modeling tools such as SAS or SQL are typically required. Critical thinking, attention to detail, and effective communication are vital soft skills for interpreting data and collaborating with stakeholders. These abilities are crucial for building accurate risk models, informing strategic decisions, and ensuring regulatory compliance in financial institutions.

How does a Credit Risk Data Scientist typically collaborate with other teams within a financial institution?

Credit Risk Data Scientists often work closely with credit analysts, risk managers, and IT professionals to develop, validate, and implement models that assess borrower risk. They frequently participate in cross-functional meetings to translate complex analytical findings into actionable business insights. Collaboration with compliance and regulatory teams is also common to ensure that risk models meet current regulatory standards. Effective communication and teamwork are essential, as the role bridges technical model development and practical risk management decisions.

What is Credit Risk Data Science?

Credit Risk Data Science is a specialized field that uses statistical analysis, machine learning, and data modeling techniques to assess and predict the likelihood that a borrower will default on a loan or credit obligation. Professionals in this field analyze large datasets from financial transactions, credit reports, and market trends to develop models that help financial institutions make informed lending decisions. Their work helps manage risk, set appropriate interest rates, and comply with regulatory standards. By leveraging advanced analytics, credit risk data scientists play a crucial role in minimizing losses and maximizing profitability for banks and lenders.
What are popular job titles related to Credit Risk Data Science jobs in Utah? For Credit Risk Data Science jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Utah look for? The top searched job categories for Credit Risk Data Science jobs in Utah are:
What cities in Utah are hiring for Credit Risk Data Science jobs? Cities in Utah with the most Credit Risk Data Science job openings:
Credit Risk Data Science jobs near you
Director of Model Validation

Director of Model Validation

First Electronic Bank

Salt Lake City, UT • On-site

$16.75 - $23/hr

Full-time

Posted 3 days ago

Job description

Job Type
Full-time
Description
At First Electronic Bank (FEB), we are driven by the purpose to make credit accessible to everyday Americans, and their businesses. Partnering with some of the most innovative FinTech companies in the nation, we offer a wide range of consumer and commercial credit products on a national basis. Offering revolving lines of credit, private-label credit cards, installment financing programs and more, FEB's engages with strategic, collaborative partnerships, promoting services and products to provide the most beneficial consumer and commercial financing solutions.
We're looking for a Director of Model Validation to lead the Model Risk Management (MRM) function and ensure the integrity and performance of the models that power our lending products with our Strategic Partners. In this role, you'll lead the department and set the directive for the Bank to oversee the validation of models and strategies used to underwrite products like small business loans, credit cards, and personal unsecured installment loans and lines of credit.
Reporting to the Head of Credit Risk and Portfolio Analytics, you'll set the strategic direction for model governance and validation across our FinTech partnerships-covering products like small business loans, credit cards, and personal installment loans.
This is a high-impact leadership role where you'll shape policy, manage a talented team, and collaborate with internal and external stakeholders to ensure regulatory compliance and model excellence.
What You'll Do:
  • Own and manage the Bank Strategic Partner Model Risk Management function, including Model Governance policies and procedures.
  • Continuously enhance processes and controls to ensure compliance with regulatory requirements.
  • Mentor, develop and lead a team of Model Validation Analysts and Managers responsible for validation credit risk, fraud detection, and behavioral credit models across our Fintech partnerships.
  • Oversee and maintain the internal model inventory for the Strategic Partner products.
  • Lead and improve loan portfolio performance monitoring processes using data feeds and visualization tools such as PowerBI.
  • Collaborate with external data science and modeling teams, providing guidance on model development and ensuring thorough documentation and adherence to Model Risk Management standards.
  • Partner with Compliance to define and strengthen standards that ensure fair lending practices and regulatory compliance.
  • Support due diligence efforts by assigning model validation subject matter experts to the process.
  • Serve as primary point of contact during regulatory exams (FDIC, UDFI) for model risk management activities.
  • Work with external vendors and legal counsel to validate modeling techniques and align with industry best practices.
  • Participate in Bank Committees and Advisory Groups to provide strategic input on model risk initiatives.

Requirements
What We're Looking For:
  • Advanced degree in a quantitative field or equivalent practical experience in data science, statistical modeling, or quantitative analysis.
  • 5+ years of experience in regulated banking or financial services industry.
  • 3+ years of direct people management experience in a quantitative discipline.
  • Strong knowledge of regulatory requirements for model risk management (SR 11-7).
  • Experience participating in, or leading, supervised regulatory exams.
  • Proven experience developing and validating statistical and machine learning models for credit risk.
  • Excellent communication skills, with the ability to translate complex technical concepts into clear, actionable insights for diverse audiences.
  • Experience presenting to executive leadership and supporting strategic committees.
  • Adaptable, collaborative mindset-ready to thrive in a fast-paced growing organization.
  • Proficiency in programming languages such as Python, R, SAS, or SQL a plus.

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