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Credit Risk Data Science Jobs in Iowa (NOW HIRING)

Aegon

Head of Credit Risk

Cedar Rapids, IA

Own and develop credit risk elements of the enterprise risk framework to ensure alignment with ... Proficient in financial modeling, data analysis, and portfolio management software * Forward ...

DataAnnotation

Credit Risk Manager

Nevada, IA · Remote

$50 - $60/hr

We are looking for a Credit Risk Manager to join our team at DataAnnotation to train AI models. You ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

Big River Steel LLC

Manager - Credit, BRS

Osceola, IA · On-site

Review and analyze customer financial statements, interim financials, borrowing base data, trade and bank references, and other relevant information to assess credit risk * Evaluate customer ...

Tractor Zoom

Be Seen First

Senior Data Scientist

Des Moines, IA · On-site

$120K - $145K/yr

We empower Farm Credit Associations, Farm Service Agencies, banks, equipment dealerships ... Bachelor's degree in Statistics, Mathematics, Engineering, Computer Science or related field ...

B2E Marketing

Marketing Data Scientist

Des Moines, IA · On-site

Bachelor's degree in Data Analytics or a related field. * 25 years of experience in data science ... Credit and criminal background verification required on all applicants. B2E Data Marketing is an ...

New

LCS

VP, Data & AI

Des Moines, IA · On-site

... data science, data governance, and AI. This leader will define and execute the enterprise AI ... risk, governance, security, ethics, and business impact • Demonstrated ability to lead change ...

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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.
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Credit Risk Data Science jobs near you

Credit Data Analyst (Mid-Level)

Watercress Financial Group LLC

West Des Moines, IA • On-site

Full-time

Posted 7 days ago

Job description

Description:

The Credit Data Analyst is responsible for the ongoing credit performance, risk management and delinquency monitoring of the company’s home improvement loan portfolio. This role contributes heavily to the end-to-end monitoring, analysis, and optimization of loan performance, ensuring that repayment, delinquency, cure rates, and charge-offs remain within the company’s risk appetite and financial targets.


The Credit Data Analyst is a member of the analytical credit risk team focused on development, testing and implementation of new or enhanced strategies to improve future loan portfolio performance.


Watercress Financial is a home improvement lender originating across the United States. Candidates should be comfortable working in a highly entrepreneurial company where smart ideas, fast analysis, and thinking ahead are high-value personal traits.


RESPONSIBILITIES

  • Create and maintain monitoring reporting for consumer loan portfolio performance
  • Provide analysis and back-testing to minimize delinquency and charge off, while optimizing loan approval, look-to-book rates, and repayment rates.
  • Detect emerging credit risk trends in the economy, market or portfolio, and provide strategic recommendation to reduce credit risk or optimize profitability
  • Provide transparent, defensible reporting to executive leadership and risk committees
  • Create, maintain and enhance: loan loss forecasting, prepayment models, roll rate analysis, transition rate analysis.


QUALIFICATIONS

  • 4yr degree Finance, Accounting, Engineering, Actuarial, Com-Sci or other analytical field (Associates Degree with commensurate experience also considered)
  • Two or more years in a consumer lending portfolio management, FP&A, risk, data analysis/modeling or similar role
  • Confident working independently , detailed oriented
  • Strong working knowledge of: credit bureau data, consumer loan portfolio, loan repayment and delinquency behavior


KNOWLEDGE AND SKILLS

  • Experience with consumer loan capital markets, FP&A, loan securitization
  • MS Excel, Microsoft Power stack (PowerBI, PowerQuery, PowerPivot, PowerAutomate) and SQL
  • MLL, boosted/ensemble and/or chat models
Requirements: