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Credit Risk Data Science Jobs in Farmington, MI (NOW HIRING)

Ford Motor Company

Data Governance Analyst

Dearborn, MI · On-site

... risk management, automotive, and consulting. You will help ensure customer and enterprise data are ... Bachelor's degree in Information Technology, Computer Science, Management Information Systems ...

Ford Motor Company

Data Governance Analyst

Dearborn, MI · On-site

... and security, risk management, automotive, and consulting. You will help ensure customer and ... Understand and support data-security requirements across functional areas, including Ford Credit ...

KLA Corporation

Analyst, Collections

Ann Arbor, MI · Hybrid

$60K - $103K/yr

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with ... Partner with Credit Analysts on customer financial reviews and risk assessments. Dispute Resolution

Orbotech

Analyst, Collections

Ann Arbor, MI · Hybrid

$60K - $103K/yr

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with ... Partner with Credit Analysts on customer financial reviews and risk assessments. Dispute Resolution

KLA Corporation

Analyst, Collections

Ann Arbor, MI · On-site

$60K - $103K/yr

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with ... Partner with Credit Analysts on customer financial reviews and risk assessments. Dispute Resolution

Kla

Analyst, Collections

Ann Arbor, MI · Hybrid

$60K - $103K/yr

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with ... Partner with Credit Analysts on customer financial reviews and risk assessments. Dispute Resolution

Deloitte

Financial Risk Senior Consultant

Detroit, MI

$115K/yr

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 ...

Randstad Digital

Technical Project Manager

Ann Arbor, MI · On-site

$45 - $50/hr

... data quality,data science,data science solutions,infrastructure,data privacy regulations,program management experience,Project Development,risks,Risk Mitigation,Stakeholder Management Equal ...

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Credit Risk Data Science information

See Farmington, MI salary details

$36.4K

$112.1K

$194.3K

How much do credit risk data science jobs pay per year?

As of Sep 11, 2026, the average yearly pay for credit risk data science in Farmington, MI is $112,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,200.00 and $138,300.00 per year, depending on experience, location, and employer.

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 Farmington, MI?

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

What job categories do people searching Credit Risk Data Science jobs in Farmington, MI look for?

The top searched job categories for Credit Risk Data Science jobs in Farmington, MI are:

What cities near Farmington, MI are hiring for Credit Risk Data Science jobs?

Cities near Farmington, MI with the most Credit Risk Data Science job openings:

Credit Risk Data Science jobs near you
Infographic showing various Credit Risk Data Science job openings in Farmington, MI as of September 2026, with employment types broken down into 100% Full Time. Highlights an 85% In-person, 5% Hybrid, and 10% Remote job distribution, with an average salary of $112,060 per year, or $53.9 per hour.

Data Scientist (Statistician) - Direct Hire

Ann Arbor, MI • On-site

US Department of the Treasury
Public Administration • 10K+ employees
Learn more about US Department of the Treasuryexternal

$125K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

Job description

WHAT IS LARGE BUSINESS AND INTERNATIONALDIVISION?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications: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 closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, 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 identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.

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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