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Credit Risk Data Science Jobs in Iowa (NOW HIRING)

Corteva Agriscience

Credit Analyst

Des Moines, IA · On-site

Conducts customer risk assessment and impact of credit terms to profitability and cash flow. And ... data needed for credit review. Additionally * Understanding of PHI Financial Services Deferred ...

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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

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 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.
What are popular job titles related to Credit Risk Data Science jobs in Iowa? For Credit Risk Data Science jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Iowa look for? The top searched job categories for Credit Risk Data Science jobs in Iowa are:
What cities in Iowa are hiring for Credit Risk Data Science jobs? Cities in Iowa with the most Credit Risk Data Science job openings:
Credit Risk Data Science jobs near you

Data Scientist-Direct Hire-6-Month Register

Criminal Investigation & Law Enforcement | IRS Careers

Des Moines, IA

$125K/yr

Other

Posted 9 days ago

Job description

WHAT IS DATA AND ANALYTICS (DA)-RESEARCH APPLIED ANALYTICS & STATISTICS (RAAS)?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position(s) are to be filled in the following area(s):
    • DAO DATA AND ANALYTICS
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.
REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the cut-off dates as shown in announcement under the 'How to Apply' section.
QUALIFICATION REQUIRMENTS: BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
AND
SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes experience performing all the following:
  • Leading data science or statistical analysis initiatives by defining project scope, analytic approach, data requirements, schedules, deliverables, or success measures; coordinating work across data, program, business, or technology stakeholders; and developing findings or recommendations for program or operational decisions.
  • Developing or applying statistical, machine learning, operations research, artificial intelligence, or other data science methods to evaluate programs, operations, compliance, or organizational performance, for example forecasting, predictive or prescriptive modeling, optimization, natural language processing or text analytics, graph or link analysis, neural networks or deep learning, or exploratory data analysis.
  • Overseeing data preparation, data quality, data governance, data certification, or analytic product delivery using programming, query, scripting, or analytic tools, such as Structured Query Language (SQL), R, Python, SAS, or equivalent tools, to support reproducible analysis, reporting, modeling, or decision-support products.
  • Experience manipulating datasets in relational databases (e.g., Compliance Data Warehouse, Enterprise Data Platform).
  • Advising managers or senior leaders on data science findings, automation opportunities, policy or program impacts, resource implications, risks, or recommended changes to processes, procedures, or operations.
  • Providing technical guidance, review, or mentoring to analysts or data scientists and preparing technical reports, briefings, presentations, or documentation that explain methods, assumptions, limitations, validation results, success measures, key performance indicators, or recommendations.
AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education
For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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