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Credit Risk Data Science Jobs in Arizona (NOW HIRING)

Data Scientist II

Tempe, AZ · On-site

$131K - $172K/yr

... risk, build higher-performing provider networks, and create a standout consumer experience in our ... Help ensure data science processes and outputs align with broader team strategies and roadmaps

Data Scientist II

Tempe, AZ · Hybrid

$131K - $172K/yr

... risk, build higher-performing provider networks, and create a standout consumer experience in our ... Help ensure data science processes and outputs align with broader team strategies and roadmaps

Review financial statements to assess risk and assign appropriate credit ratings * Maintain and ... Advanced proficiency in Microsoft Excel (pivot tables, formulas, data analysis) * Ability to ...

Review financial statements to assess risk and assign appropriate credit ratings * Maintain and ... Advanced proficiency in Microsoft Excel (pivot tables, formulas, data analysis) * Ability to ...

Principal Data Scientist

Phoenix, AZ · On-site

$150 - $210/hr

You will work at the intersection of data science, clinical context, cloud architecture, and ... Familiarity with model transparency, AI risk management, PHI-sensitive environments, auditability ...

Continuously monitor credit risk for a portfolio of accounts as new financial data, press releases, or other information becomes available throughout a company's lifecycle. * Recommend changes to ...

... risk and compliance policies and procedures. What you have: * Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other ...

Data Scientist

Scottsdale, AZ · On-site

$80K - $120K/yr

Appointment optimization * Clinical risk stratification * Patient adherence forecasting ... Master's degree in Data Science, CS, Statistics, Biomedical Informatics, or related field preferred ...

Sr. Data Analyst

Tempe, AZ · On-site

$85 - $130/hr

As a Sr. Data Analyst, you'll impact the lives of everyday people and help them go from surviving ... credit performance by finding pockets of low risk consumer where we can approve more loansUse ...

Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or ... Exposure to industry-specific domains such as ecommerce, marketing analytics, risk/fraud, supply ...

Master's degree in Computer Science, Statistics, Mathematics, Engineering, Operations Research, or ... Exposure to industry-specific domains such as ecommerce, marketing analytics, risk/fraud, supply ...

Showing results 41-60

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 Arizona?

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

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

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

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

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

Data Scientist II

Oscar Health

Tempe, AZ • On-site

$131K - $172K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 16 days ago


Oscar Health rating

6.9

Company rating: 6.9 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

260th of 311 rated insurance


Job description

Hi, we're Oscar. We're hiring a Data Scientist II to join our Data team.
Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves - one that behaves like a doctor in the family.
About the role:
Oscar's data team is focused on pushing our understanding of this complex landscape of health care and insurance business. Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members. Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product.
As a Data Scientist II you will drive data science projects across multiple teams and domains. In this role, you'll take ownership of analytical and modeling work, contribute to technical direction, and partner closely with business, engineering, product and data stakeholders to deliver impactful solutions.
This is a mid-level role for data scientists who can operate independently, manage ambiguity, and apply advanced analytics or modeling techniques with minimal oversight.
You will report into a leader on the Data team (Senior Data Scientist and above). This posting is representative of multiple roles, and final team placement will be determined during the interview process.
Work Location: This position is a hybrid role based in our New York City office, Los Angeles Office, or Tempe Office requiring a hybrid work schedule with 3 days of in-office work per week Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid
Pay Transparency: The base pay for this role is: $131,200 - $172,200 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.
Responsibilities:
  • Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions
  • Own projects end-to-end, including problem definition, implementation, validation, and iteration
  • Deliver high-quality analytical and modeling outputs with limited manager oversight
  • Collaborate closely with data science peers and cross-functional partners across business units
  • Help ensure data science processes and outputs align with broader team strategies and roadmaps
  • Provide guidance or informal mentorship to junior data scientists or analysts when needed
  • Contribute to improving data science practices, tooling, and documentation

Requirements:
  • 3+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both)
  • 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data
  • 2+ years of experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing

Bonus points:
  • Master's degree in a quantitative or technical field
  • Knowledge of or previous work experience in health care or health insurance
  • Experience mentoring or supporting junior team members
  • Experience deploying or supporting models in production environments

This is an authentic Oscar Health job opportunity. Learn more about how you can safeguard yourself from recruitment fraud here.
At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives.
Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements.
Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts.
Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant's disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team (accommodations@hioscar.com) to make the need for an accommodation known.
California Residents: For information about our collection, use, and disclosure of applicants' personal information as well as applicants' rights over their personal information, please see our Privacy Policy.

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