1

Credit Risk Data Science Jobs in Arizona (NOW HIRING)

Own assigned data science projects and major workstreams from analytical planning through ... credit check ( applicable for certain positions) and reference verification. This reflects ...

New

Analyze financial statements and third-party financial data for public and private domestic and international customers to assess credit risk * Evaluate customer creditworthiness and recommend credit ...

Wells Fargo is seeking a Lead Data Science Consultant, focused on the delivery of advanced ... They are accountable for execution of all applicable risk programs (Credit, Market, Financial ...

New

Requirements: * Bachelor's degree required in Mathematics, Data Science, Computer Science ... Familiarity with model governance, model risk management, compliance, or regulatory frameworks is a ...

... risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving ...

... risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving ...

... risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving ...

... risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving ...

... risk management policies and regulatory requirements. You will influence the future of data science at USAA by researching emerging technologies, identifying opportunities for innovation, and driving ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ ยท On-site

$101K - $137K/yr

Our data science and analytics team automates everything Carvana does from modeling consumer ... Whether we're assessing credit risk, optimizing inventory and pricing strategies, or building AI ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ ยท On-site

$101K - $137K/yr

Our data science and analytics team automates everything Carvana does from modeling consumer ... Whether we're assessing credit risk, optimizing inventory and pricing strategies, or building AI ...

Senior Data Engineer, Predictive Modeling

Tempe, AZ ยท On-site

$101K - $137K/yr

Our data science and analytics team automates everything Carvana does from modeling consumer ... Whether we're assessing credit risk, optimizing inventory and pricing strategies, or building AI ...

Data Scientist II

Tempe, AZ ยท 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

Showing results 21-40

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:

Manager - Data Science

Phoenix, AZ โ€ข On-site

Other

Posted 2 days ago

New


Job description

Position Summary

At Caris, we understand that cancer is an ugly word-a word no one wants to hear, but one that connects us all. That is why we're not just transforming cancer care- we're changing lives. We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day: "What would I do if this patient were my mom?" That question drives everything we do. But our mission doesn't stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare- driven by innovation, compassion, and purpose. Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.

The Manager works within priorities and practices established by Data Science leadership and partners closely with scientific, technical, product, and commercial teams.

Job Responsibilities
  • Manage and mentor an assigned team of data scientists, including coordinating day-to-day priorities and supporting professional development.
  • Own assigned data science projects and major workstreams from analytical planning through validation and delivery.
  • Develop project plans and coordinate reviews, dependencies, handoffs, timelines, and success criteria.
  • Translate scientific, clinical, product, and commercial questions into appropriate analytical approaches and deliverables.
  • Apply and reinforce established standards for reproducibility, validation, documentation, code quality, and statistical and machine-learning analyses.
  • Review analytical methods, code, validation results, and model artifacts for scientific rigor and quality.
  • Facilitate analytical vetting with computational biology, bioinformatics, translational science, clinical subjectโ€‘matter experts, and other scientific partners.
  • Coordinate crossโ€‘functional work with Engineering, Product, Commercial, Business Development, Clinical Decision Support, and related teams.
  • Identify projectโ€‘level priority or resource conflicts and escalated to Data Science leadership when needed.
  • Communicate analytical methods, limitations, progress, and results to technical and nonโ€‘technical stakeholders.
  • Evaluate relevant advances in data science, statistics, and machine learning for use within assigned projects.
  • Improve teamโ€‘level delivery practices to increase quality, throughput, predictability, and partner trust.
Required Qualifications
  • PhD in data science, statistics, biostatistics, computer science, computational biology, bioinformatics, or a related quantitative field.
  • Five or more years of relevant experience, including project, team, or people leadership in biomedical data science.
  • Demonstrated experience leading data science projects from problem definition through validated delivery.
  • Advanced proficiency in Python and working proficiency in SQL.
  • Strong foundation in statistical modeling, machine learning, data visualization, and scientific interpretation.
  • Experience analyzing large, complex biomedical datasets, such as genomic, proteomic, clinical, or other multimodal data.
  • Experience developing reproducible analytical workflows with appropriate validation, documentation, and quality controls.
  • Ability to review technical work and mentor data scientists.
  • Strong written and verbal communication skills, including the ability to explain nuanced technical material to varied audiences.
  • Ability to coordinate competing project priorities and deliver high-quality work in a collaborative environment.
Preferred Qualifications
  • Experience in oncology, precision medicine, or immunology.
  • Experience integrating multimodal molecular and clinical data.
  • Experience developing molecular signatures, derived data assets, research deliverables, data products, or clinical decision support analyses.
  • Experience in an industry or customerโ€‘facing environment.
  • Experience with cloud computing or highโ€‘performance computing.
  • Familiarity with production machineโ€‘learning or MLOps practices.
  • Experience developing agentic AI applications or workflows, including agent orchestration, tool integration, evaluation, and human oversight.
Physical Demands

Ability to work at a computer for extended periods.

Training

Job-specific, safety, and compliance training will be assigned based on the responsibilities of the position. Occasional travel may be required. Occasional evening or weekend work may be required.

Conditions of Employment

Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check ( applicable for certain positions) and reference verification.

This job description reflects managementโ€™s assignment of essential functions. Nothing in this job description restricts managementโ€™s right to assign or reassign duties and responsibilities to this job at any time.

Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.

Caris Life Sciences is a leading innovator in molecular science and artificial intelligence focused on fulfilling the promise of precision medicine through quality and innovation. Caris is committed to quality and excellence at our stateโ€‘ofโ€‘theโ€‘art laboratories. Learn more about our tissue lab and the advanced technologies that are helping improve the lives of cancer patients.

#J-18808-Ljbffr