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Credit Risk Data Science Jobs in Oklahoma (NOW HIRING)

Data Scientist

Tulsa, OK · On-site

$80K - $120K/yr

Build customer-facing, live risk dashboards that visualize jobsite risk metrics and safety insights. EDUCATION/EXPERIENCE: Position requires a Master's degree (or foreign equivalent) in Data Science ...

... data, or other required information Write comprehensive credit analyses evaluating borrower ... risk in assigned portfolio and prepare quarterly reports on sensitive names Support ad hoc ...

Evaluates the credit risk of new and existing customers through analysis of financial data, payment history, and related credit information. * Recommends appropriate credit limits and payment terms ...

New

Evaluates the credit risk of new and existing customers through analysis of financial data, payment history, and related credit information. * Recommends appropriate credit limits and payment terms ...

Evaluates the credit risk of new and existing customers through analysis of financial data, payment history, and related credit information. * Recommends appropriate credit limits and payment terms ...

Evaluates the credit risk of new and existing customers through analysis of financial data, payment history, and related credit information. * Recommends appropriate credit limits and payment terms ...

$110K/yr

LoanTrak, ACBS, Clearpar, Loantracker, Kiwis) Assist in regular monitoring of trading limits for Americas trading books with weekly reporting to RPC/Credit Risk Liaise directly with other secondary ...

Manager Credit & Collection

Tulsa, OK · On-site

$70K - $106K/yr

Key Responsibilities: • Credit Risk Assessment: Evaluate the creditworthiness of current and potential customers by reviewing financial statements, credit reports, and other relevant data to ...

Manager Credit & Collection

Tulsa, OK · On-site

$70K - $106K/yr

Credit Risk Assessment: Evaluate the creditworthiness of current and potential customers by reviewing financial statements, credit reports, and other relevant data to determine credit risk.

This role spans both traditional data science responsibilities and emerging generative AI ... Managing Risk - Assessing and effectively managing all of the risks associated with their business ...

Partner with cross-functional stakeholders (legal, compliance, security, data science, engineering) to drive timely remediation and risk resolution. Continuous Improvement & Portfolio Insights ...

... risk. * Design and evaluate experiments or comparative studies to determine whether observed ... Bachelor's degree in Data Science, Computer Science, Computer Engineering, Mathematics or related ...

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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 Oklahoma? For Credit Risk Data Science jobs in Oklahoma, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Oklahoma look for? The top searched job categories for Credit Risk Data Science jobs in Oklahoma are:
What cities in Oklahoma are hiring for Credit Risk Data Science jobs? Cities in Oklahoma with the most Credit Risk Data Science job openings:

$80K - $120K/yr

Full-time

Posted 3 days ago


Job description

JOB SUMMARY:
Safety Radar Inc. seeks a Data Scientist to develop AI modules to evaluate customer safety and risk data, perform metric analysis, and interpret outputs. Contribute to the development of AI analysis frameworks to ensure accurate and consistent results across all customer data sources. Perform analysis of AI results for internal use to detect and fix abnormalities before transitioning AI outputs to production environment. Write, retain, and improve SQL scripts to query and format outputs of AI analysis blocks. Conduct statistical analysis of Causal Factors to identify correlations between Potential Severity and PSIF Exposure. Conduct ad-hoc data analysis tasks to drive internal decisions related to AI tools and computing costs. Build customer-facing, live risk dashboards that visualize jobsite risk metrics and safety insights.
EDUCATION/EXPERIENCE:
Position requires a Master's degree (or foreign equivalent) in Data Science, Business Analytics, or a related technical field, and 2 years of statistical analysis experience. Experience must include: 1 year of experience using data visualization tools; 1 year of experience using SQL to extract, transform, and load data for analysis; 1 year of experience utilizing Python, including utilizing pandas, NumPy, SciPy, Matplotlib, seaborn, and scikit-learn; and 3 months of experience utilizing AI large language model prompts. Telecommuting is available up to 2 days per week.
Job Location: Tulsa, OK
Rate of Pay: $80,000.00 - $120,000.00 annually
To apply, please email your resume and cover letter to hr@safetyradar.com and reference Job Code: 107.
Safety Radar is proud to be an equal-opportunity employer. We do not discriminate in hiring or any employment decisions based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or any other legally protected characteristic. We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans during the application process. If you need assistance or an accommodation due to a disability, you may contact hr@safetyradar.com.
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