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Credit Risk Jobs in Arizona (NOW HIRING)

QXO

Credit Director

Glendale, AZ · On-site

QXO is seeking a Credit Director to lead credit strategy, risk management, and accounts receivable performance while supporting profitable business growth. This role will oversee a team of Credit ...

QXO

Credit Director

Glendale, AZ · On-site

QXO is seeking a Credit Director to lead credit strategy, risk management, and accounts receivable performance while supporting profitable business growth. This role will oversee a team of Credit ...

Expeditors

Credit Specialist

Scottsdale, AZ

Review financial statements to assess risk and assign appropriate credit ratings * Maintain and monitor a portfolio of high-risk accounts, ensuring timely follow-up, documentation, and proactive ...

Expeditors

Credit Specialist

Scottsdale, AZ · On-site

Review financial statements to assess risk and assign appropriate credit ratings * Maintain and monitor a portfolio of high-risk accounts, ensuring timely follow-up, documentation, and proactive ...

Expeditors

Credit Specialist

Scottsdale, AZ

Review financial statements to assess risk and assign appropriate credit ratings * Maintain and monitor a portfolio of high-risk accounts, ensuring timely follow-up, documentation, and proactive ...

US Bank

Business Banking Senior Credit Officer

Tempe, AZ · On-site

$193K - $227K/yr

Senior Credit Risk Management role responsible for leading a team of Credit Approval Officers supporting Business Banking lending in the Midwest and East regions. Portfolio composition includes C&I ...

Western Alliance Bank

Credit Analyst

Mesa, AZ

Review client financials and perform sensitivity analysis to evaluate credit risk in connection with Bank structures. Prepare in-depth reports providing plans of action based on qualitative and ...

Disability Solutions

Credit Analyst

Phoenix, AZ · On-site

Review client financials and perform sensitivity analysis to evaluate credit risk in connection with Bank structures. Prepare in-depth reports providing plans of action based on qualitative and ...

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All JobsCredit Risk JobsCredit Risk Jobs in Arizona

Credit Risk information

See Arizona salary details

$46.6K

$101.9K

$170.5K

How much do credit risk jobs pay per year?

As of Jun 6, 2026, the average yearly pay for credit risk in Arizona is $101,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,900.00 and $132,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Credit Risk Analyst, and why are they important?

To thrive as a Credit Risk Analyst, you need strong analytical skills, a solid understanding of financial statements, and a background in finance, economics, or a related field, often supported by a relevant degree or certification (such as FRM or CFA). Familiarity with risk assessment tools, financial modeling software, and credit rating systems is typically required. Attention to detail, critical thinking, and effective communication are essential soft skills for interpreting data and presenting risk assessments to stakeholders. These skills and qualities are crucial for making informed decisions that minimize financial losses and ensure sound lending practices.

What is the difference between Credit Risk vs Credit Analyst?

AspectCredit RiskCredit Analyst
Primary FocusAssessing the likelihood of borrower default to manage overall credit riskAnalyzing credit data to determine creditworthiness of individual applicants
Work EnvironmentRisk management teams, financial institutions, credit departmentsBanking, lending institutions, financial services
Required CredentialsOften requires risk management certifications, finance degreesFinance or accounting degrees, certifications like CFA or credit-specific courses

While both roles involve understanding credit, Credit Risk focuses on managing the overall risk exposure of an organization, whereas a Credit Analyst evaluates individual credit applications to determine approval. Both roles are essential in the lending process but differ in scope and responsibilities.

What is credit risk and what does a credit risk professional do?

Credit risk refers to the possibility that a borrower or counterparty will fail to meet their financial obligations, such as repaying a loan or making payments on time. Credit risk professionals analyze financial data, assess the creditworthiness of individuals or companies, and help set lending policies to minimize potential losses for banks or financial institutions. They use various models and tools to evaluate risk, monitor existing loans, and recommend strategies to mitigate exposure. Their work is essential for maintaining the financial health and stability of lending organizations.

What are some typical challenges faced by professionals in credit risk roles, and how can they be addressed?

Credit risk professionals often encounter challenges such as assessing the creditworthiness of new and existing clients, keeping up with rapidly changing market conditions, and managing large volumes of data to make informed decisions. To address these, it's important to stay updated on industry trends, develop strong analytical and communication skills, and leverage advanced risk assessment tools. Collaborating closely with colleagues in underwriting, sales, and compliance teams also helps ensure well-rounded risk evaluations and consistent application of policies.
What are the most commonly searched types of Credit Risk jobs in Arizona? The most popular types of Credit Risk jobs in Arizona are:
What are popular job titles related to Credit Risk jobs in Arizona? For Credit Risk jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Credit Risk jobs in Arizona look for? The top searched job categories for Credit Risk jobs in Arizona are:
What cities in Arizona are hiring for Credit Risk jobs? Cities in Arizona with the most Credit Risk job openings:
Credit Risk jobs near you
Infographic showing various Credit Risk job openings in Arizona as of May 2026, with employment types broken down into 85% Full Time, 13% Part Time, and 2% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $101,868 per year, or $49 per hour.
Senior Data Scientist, Predictive Modeling, Credit & Risk

Senior Data Scientist, Predictive Modeling, Credit & Risk

Carvana

Tempe, AZ • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 13 days ago

Carvana rating

6.7

Company rating: 6.7 out of 10

Based on 261 frontline employees who took The Breakroom Quiz

199th of 713 rated retailers

Job description

About Carvana...
At Carvana, we're changing the way people buy and sell cars. With an ambitious vision and a fundamentally different approach designed to be fun, fast, and fair, Carvana became the fastest-growing automotive retailer in history. We expanded nationally, went public on the New York Stock Exchange, sold our 1 millionth car, and reached the Fortune 500, all in just eight years.
Today, with 4 million retail customers and counting, Carvana is both the fastest-growing and the most profitable public automotive retailer, and we're just getting started. We continue to raise the bar for our customers as we tackle the enormous opportunity still ahead in the largest consumer vertical.
Working here means being part of a team that embraces change, celebrates creative problem solving, and always strives to be better. At Carvana, you'll have the opportunity to take on meaningful challenges, learn quickly, and help shape the future of automotive retail. If you're driven to grow and make an impact as part of a collaborative team, you'll fit right in. Learn more about what it's like to work here from the people that already do.
Work Model: This is a 100% on-site role at our Tempe office, Monday through Friday.
About the Role
This role sits within Carvana's Credit & Risk modeling space, working on high-impact predictive models that inform risk assessment and decisioning across the business.
We are looking for a senior individual contributor who will help advance the technical capabilities of our core credit and risk models by developing, validating, and productionizing new modeling techniques and data signals.
Success in this role comes from steady, compounding improvement-introducing new ideas pragmatically, proving value early, and iterating toward more sophisticated approaches over time. While the work will focus on flagship credit and risk models, successful techniques and signals are expected to scale outward to other models and teams through shared workflows and modeling infrastructure.
This role is well suited for someone who operates comfortably at the intersection of advanced modeling and real-world delivery to balance tradeoffs between complexity and business objectives.
What You'll Be Doing
  • Improve core credit and risk models through a sequence of incremental advancements in accuracy, robustness, and coverage over time.
  • Leverage a wide range of structured and unstructured data sources across multiple modalities to drive sustained improvements in model accuracy and decision quality.
  • Design, train, and deploy advanced machine learning models, including (but not limited to) gradient boosting, representation learning, embeddings, and transformer-based approaches.
  • Use high-impact models as a testing ground for new techniques and data modalities, validating which ideas deliver measurable lift in production.
  • Build and apply rigorous evaluation frameworks (offline validation, backtests, simulations, online experiments) to guide iteration and decision-making.
  • Exercise strong judgment about model complexity and tradeoffs, balancing sophistication with reliability and maintainability.
  • Partner closely with data engineering and platform teams to ensure models are production-ready, scalable, monitorable, and maintainable.
  • Translate successful work into reusable patterns, abstractions, or signals that can be adopted across other modeling efforts.
  • Serve as a technical leader within the Predictive Modeling organization through design reviews, code reviews, and informal mentorship.

What You Should Have
  • 5-8+ years of experience building and deploying predictive models in production environments.
  • A demonstrated track record of delivering models and improving them iteratively over time, not just developing them offline.
  • Strong experience with modern machine learning techniques (e.g., LightGBM/XGBoost, neural networks, representation learning).
  • Excellent statistical intuition, including comfort reasoning about bias/variance tradeoffs, generalization, and experimental validity.
  • Fluency in Python and SQL, with production-quality coding standards.
  • Proven ability to take ambiguous, open-ended modeling problems from idea → experiment → production impact.
  • Bachelor's degree in Computer Science, Statistics, Math, Quantitative Economics, or similar field from an accredited undergraduate institution required.

If would also be great if you had
  • Hands-on experience with embeddings, transformers, or other deep representation models in real-world systems.
  • Experience integrating unstructured or semi-structured data (text, images, documents, device signals) into predictive models.
  • Familiarity with model monitoring, drift detection, and retraining strategies for high-impact decision systems.
  • Experience working in credit, risk, fraud, underwriting, or similar high-stakes modeling environments.

Notes on Experience
  • Research experience is a plus only if paired with a strong bias toward delivery and production impact.

What Success Looks Like
Over time, success in this role is reflected by:
  • Measurable improvements in the accuracy, robustness, or coverage of core credit and risk models.
  • New modeling techniques or data signals that transition from experimentation into sustained production use.
  • Clear patterns or abstractions that enable other teams to adopt and build on this work.
  • Strong alignment between modeling advances and real business outcomes.

What we'll offer in return
  • Full-Time Salary Position with a competitive salary.
  • Medical, Dental, and Vision benefits.
  • 401K with company match.
  • A multitude of perks including student loan payments, discounts on vehicles, benefits for your pets, and much more.
  • A great wellness program to keep you healthy and happy both physically and mentally.
  • Access to opportunities to expand your skill set and share your knowledge with others across the organization.
  • A company culture of promotions from within, with a start-up atmosphere allowing for varied and rapid career development.
  • A seat in one of the fastest-growing companies in the country.

Legal Stuff
Hiring is contingent on passing a complete background check. This role is eligible for visa sponsorship.
Carvana is an equal employment opportunity employer. All applicants receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, marital status, national origin, age, mental or physical disability, protected veteran status, or genetic information, or any other basis protected by applicable law. Carvana also prohibits harassment of applicants or employees based on any of these protected categories.
Please note this job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.

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About Carvana

Sourced by ZipRecruiter

At Carvana, we sell cars, but we're not salespeople. Since 2013, we've been making it our mission to change the way people buy cars. We saw a huge problem with how much it can suck to buy a car the traditional way, so we committed ourselves to tackling one of the largest, yet-to-be-disrupted markets in the world - the $1T per year U.S. car market (yes, that's $Trillion with a "T").

Industry

Automobile dealers

Company size

5,001 - 10,000 Employees

Headquarters location

Tempe, AZ, US

Year founded

2011

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