... Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the ... credit risk; querying and aggregating data from a database, performing trend analysis, and ...
... Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the ... credit risk; querying and aggregating data from a database, performing trend analysis, and ...
... data science in Python, R or Spark; developing comprehensive risk management reports from large datasets; and experience with consumer financial products such as credit cards, lending products ...
... data science in Python, R or Spark; developing comprehensive risk management reports from large datasets; and experience with consumer financial products such as credit cards, lending products ...
... data science in Python, R or Spark; developing comprehensive risk management reports from large datasets; and experience with consumer financial products such as credit cards, lending products ...
... data science in Python, R or Spark; developing comprehensive risk management reports from large datasets; and experience with consumer financial products such as credit cards, lending products ...
AVP, Credit Model Development
$100K - $170K/yr
... Data Science, or a related quantitative field. * Approximately 3+ years of hands-on experience as a model developer or model validator, specifically within financial services, credit risk, or fraud ...
AVP, Credit Model Development
$100K - $170K/yr
... Data Science, or a related quantitative field. * Approximately 3+ years of hands-on experience as a model developer or model validator, specifically within financial services, credit risk, or fraud ...
... Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the ... credit risk; querying and aggregating data from a database, performing trend analysis, and ...
... Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the ... credit risk; querying and aggregating data from a database, performing trend analysis, and ...
AVP, Credit Model Development
Draper, UT · On-site
... Data Science, or a related quantitative field. * Approximately 3+ years of hands-on experience as a model developer or model validator, specifically within financial services, credit risk, or fraud ...
AVP, Credit Model Development
Draper, UT · On-site
... Data Science, or a related quantitative field. * Approximately 3+ years of hands-on experience as a model developer or model validator, specifically within financial services, credit risk, or fraud ...
... Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the ... credit risk; querying and aggregating data from a database, performing trend analysis, and ...
... Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the ... credit risk; querying and aggregating data from a database, performing trend analysis, and ...
... data science in Python, R or Spark; developing comprehensive risk management reports from large datasets; and experience with consumer financial products such as credit cards, lending products ...
... data science in Python, R or Spark; developing comprehensive risk management reports from large datasets; and experience with consumer financial products such as credit cards, lending products ...
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 ...
Quick apply
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 ...
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 ...
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 ...
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 ...
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 ...
Senior Credit Analyst
Pleasant Grove, UT · On-site
This role will collaborate directly with Risk, Compliance, Legal, and external program fintechs ... Comfortable drawing conclusions from portfolio data and performance trends. * Thrives in ambiguity.
Senior Credit Analyst
Pleasant Grove, UT · On-site
This role will collaborate directly with Risk, Compliance, Legal, and external program fintechs ... Comfortable drawing conclusions from portfolio data and performance trends. * Thrives in ambiguity.
Senior Credit Analyst
Pleasant Grove, UT · On-site
This role will collaborate directly with Risk, Compliance, Legal, and external program fintechs ... Comfortable drawing conclusions from portfolio data and performance trends. * Thrives in ambiguity.
Senior Credit Analyst
Pleasant Grove, UT · On-site
This role will collaborate directly with Risk, Compliance, Legal, and external program fintechs ... Comfortable drawing conclusions from portfolio data and performance trends. * Thrives in ambiguity.
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
Mathematics, statistics, computer science, data science or field directly related to the position ... If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP ...
Mathematics, statistics, computer science, data science or field directly related to the position ... If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
... risk management practices, collateral, risk grading accuracy, and loan documentation. If you want ... Analyze detailed financial data and spreads to quickly determine repayment capacity and ability to ...
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 ...
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 ...
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 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:
Risk - Salt Lake City - Associate, Software Engineering - 777858
Salt Lake City, UT
Other
Posted 23 days ago
Goldman Sachs rating
8.2
Based on 26 frontline employees who took The Breakroom Quiz
40th of 146 rated banks
Job description
Job Duties: Associate, Software Engineering with Goldman Sachs & Co. LLC in Salt Lake City, Utah. Provide data-driven insights and effective technologies for firmwide risk management. Identify, design, and implement the best means of delivering risk information through compelling narratives, tools and visualizations to increase understanding and awareness of risk. Assist with innovating and designing new analytics and visuals, leveraging internal and external programming languages and software. Analyze, visualize, and oversee sets of data used in risk management and control functions. Provide a quantitative application to storytelling, leveraging risk engineering processes to maximize significance, quality, efficiency, speed, and reliability while ensuring clear accountability and attribution. Perform anomaly detections in large data sets, investigating the cause and recommending corrective actions. Work in close collaboration with bankers, traders, and portfolio managers as well as risk modelers and technology across the firm.
Job Requirements: Master's degree (U.S. or foreign equivalent) in Mathematics, Finance, Electronics & Communications Engineering, Computer Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the job offered or in a related field OR Bachelor's degree (U.S. or foreign equivalent) in Mathematics, Finance, Electronics & Communications Engineering, Computer Science, Statistics, Business Analytics, or a related field and three (3) years of experience in the job offered or in a related field. Prior employment must include one (1) year (with Master's degree) or three (3) years (with Bachelor's degree) with: working with users to understand business requirements to design and develop low-cost and adoptive technical solutions; risk management at a large financial institution or a consulting organization, including experience in liquidity, regulatory, or credit risk; querying and aggregating data from a database, performing trend analysis, and visualizing results within a dashboard for the analysis of financial models used in credit risk management; examining risk factors impacting credit exposure; analyzing and explaining market trends to senior risk managers and financial regulators; and working with data management, including data flows, data mining, or data modeling.
The Goldman Sachs Group, Inc., 2026. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veteran status, disability, or any other characteristic protected by applicable law.
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About Goldman Sachs
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At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.
Industry
Finance and insurance
Company size
10,000+ Employees
Headquarters location
New York, NY, US
Year founded
1869