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Credit Risk Data Science Jobs in Michigan (NOW HIRING)

General Motors

Staff Data Scientist

Warren, MI · On-site

... risk reduction, or improved operational decisions. * Balance analytical sophistication with usability, speed to value, maintainability, and adoption. * Lead the data-science workstream from concept ...

General Motors

Staff Data Scientist

Warren, MI

... risk reduction, or improved operational decisions. * Balance analytical sophistication with usability, speed to value, maintainability, and adoption. * Lead the data-science workstream from concept ...

Ford Motor Company

Senior Data Scientist

Dearborn, MI · On-site

Balance "doing it right" with "speed to delivery" by identifying and mitigating risk, generating ... Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research ...

Ford Motor Company

Data Scientist

Dearborn, MI · On-site

Near term vehicle line specific profit improvement or risk mitigation actions * New or expanded ... Bachelors degree Computer Science, Economics, Analytics, Business, Strategy, Finance, Mathematics ...

Deloitte

Financial Risk Manager

Detroit, MI · On-site

Join our team and use advanced data, AI, and emerging technologies with industry insights to help ... Credit Risk, Liquidity Risk, Market Risk, Capital Management/Stress Testing * Knowledge of ...

Ford Motor Company

Data Scientist

Dearborn, MI

$162K/yr

Near term vehicle line specific profit improvement or risk mitigation actions * New or expanded ... Bachelors degree Computer Science, Economics, Analytics, Business, Strategy, Finance, Mathematics ...

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Credit Risk Data Science information

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 skills and qualifications are needed to thrive as a credit risk data scientist?

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 are popular job titles related to Credit Risk Data Science jobs in Michigan?

For Credit Risk Data Science jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Credit Risk Data Science jobs in Michigan look for?

The top searched job categories for Credit Risk Data Science jobs in Michigan are:

What cities in Michigan are hiring for Credit Risk Data Science jobs?

Cities in Michigan with the most Credit Risk Data Science job openings:

Credit Risk Data Science jobs near you

Data Scientist (ARTIFICIAL INTELLIGENCE/MACHINE LEARNING)

U.S. Department of Defense (DOD)

Battle Creek, MI • On-site

$125K/yr

Full-time, Part-time

Posted 14 days ago

U.S. Department Of Defense rating

7.8

Company rating: 7.8 out of 10

Based on 538 frontline employees who took The Breakroom Quiz

28th of 49 rated military and defense

Job description

See below for important information regarding this job.
Position will be filled at any of the locations listed below. Site specific salary information as follows:
Battle Creek, MI: $125,776- $163,514
Columbus, OH: $131,245- $170,624
Dayton, OH: $130,461 - $169,604
Fort Belvoir, VA: $143,913- $187,093
New Cumberland, PA: $143,913- $187,093
Ogden, UT: $125,776- $163,514
Philadelphia, PA: $138,595- $180,178
Richmond, VA: $131,385- $170,806
Qualifications:To qualify for a Data Scientist (Artificial Intelligence/Machine Learning), your resume and supporting documentation must support:
A. Degree: Mathematics, statistics, computer science, data science or 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.
B. Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position. To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-aftercompetitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes:
  • Conducts large, agency wide, research and development reviews of metrics, measurements, and evaluation methods for emerging and existing areas of Al.
  • Utilizes data science expertise to develop algorithms and tools to support data manipulation and processing as well as the use of data visualization techniques to articulate high risk findings.
  • Ensures the Al systems are designed for auditability to manage Al risk assessment policies and principles which guide automated decisions supporting DLA business operations.
  • Provides expert advice to senior leadership and Al stakeholders to adopt new or revised policy and implementation plans resulting from Al test and evaluation integration.
  • Assesses data quality and establishes standards to validate quality criteria for data to ensure it meets the necessary requirements for Al testing and evaluation.

Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:Are you using your education to qualify? You MUST provide transcripts or other documentation to support your educational claims. Unless otherwise stated: Unofficial transcripts are acceptable at time of application.
GRADUATE EDUCATION: One academic year of graduate education is considered to be the number of credits hours that your graduate school has determined to represent one academic year of full-time study. Such study may have been performed on a full-time or part-time basis. If you cannot obtain your graduate school's definition of one year of graduate study, 18 semester hours (or 27 quarter hours) should be considered as satisfying the requirement for one year of full-time graduate study.
FOREIGN EDUCATION: If you are using education completed in foreign colleges or universities to meet the qualification requirements, you must show that the education credentials have been evaluated by a private organization that specializes in interpretation of foreign education programs and such education has been deemed equivalent to that gained in an accredited U.S. education program; or full credit has been given for the courses at a U.S. accredited college or university.Employment Type: OTHER

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