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Credit Risk Data Science Jobs in Arizona (NOW HIRING)

... credit unions to increase efficiency, manage risk and improve the member experience. Trellance ... Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Mathematics ...

What makes this team unique is its position at the intersection of data science, engineering ... Risk Modeling: Create frameworks that quantify warranty exposure, failure risk, component ...

$49K/yr

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 Modeling: Create frameworks that quantify warranty exposure, failure risk, component ... Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a ...

Risk Modeling: Create frameworks that quantify warranty exposure, failure risk, component ... Bachelors degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a ...

Risk Modeling: Create frameworks that quantify warranty exposure, failure risk, component ... Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a ...

Sr. Data Analyst

Tempe, AZ ยท On-site +1

Drive improvements in credit performance by finding pockets of low risk consumer where we can ... Qualifications What you'll bring: * 5+ years of experience in data science, quantitative business ...

Sr. Data Analyst

Tempe, AZ ยท On-site

$115K - $145K/yr

Drive improvements in credit performance by finding pockets of low risk consumer where we can ... Qualifications What you'll bring: * 5+ years of experience in data science, quantitative business ...

Sr. Data Analyst

Tempe, AZ ยท On-site +1

$115K - $145K/yr

Drive improvements in credit performance by finding pockets of low risk consumer where we can ... Qualifications What you'll bring: * 5+ years of experience in data science, quantitative business ...

Data Scientist II

Tempe, AZ ยท 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 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

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 ...

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 ...

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:

Lead AI & Data Solutions

Phoenix, AZ โ€ข On-site

Trellance, Inc.
Finance and Insuranceย โ€ขย 51 - 200 employees

Other

Posted 12 days ago


Job description

CU Rise Analytics Pvt. Ltd. is a wholly owned subsidiary of Trellance, Inc. CU Rise Analytics is an offshore development centre of Trellance Inc., working collaboratively to offer comprehensive solutions for data analytics, technology and talent to allow our credit union clients to provide high quality service to their members and remain competitive. Our core expertise lies in data science and technology, encompassing data analytics, predictive modelling, business intelligence, and technology services.

Trellance Cooperative Holdings, Inc. is a credit union cooperative and leading technology partner for credit unions. Its companies โ€“ consisting of Rise Analytics, ProBridge, Optiri and CUDX โ€“ provide innovative technology solutions for credit unions to increase efficiency, manage risk and improve the member experience. Trellanceโ€™s mission is to make sure credit unions have access to the tools and resources they need to grow, enhance member value and remain competitive in a rapidly evolving financial landscape.

We are seeking an experienced and visionary Lead โ€“ Artificial Intelligence (AI) & Data Solutions to lead the design, development, and delivery of AI-driven products, workflow agents, and advanced analytics solutions for the financial services and credit union industry. The ideal candidate will combine strong leadership, technology, and business consulting skills to drive AI strategy, solution delivery, governance, and innovation initiatives.

This role will be responsible for managing a team of AI Engineers, Software Engineers, Data Engineers, and Business Analysts while partnering with business stakeholders, clients, and executive leadership to identify, prioritize, and implement AI use cases that deliver measurable business value.

AI Solution Delivery
  • Lead the design, development, and deployment of AI-powered applications, workflow agents, semantic models, and advanced analytics solutions.
  • Oversee implementation of solutions using Microsoft Azure AI Foundry, Azure OpenAI, Snowflake, Databricks, Microsoft Fabric, and related technologies.
  • Guide teams in building Retrieval Augmented Generation (RAG) architectures, semantic search solutions, AI-to-SQL capabilities, and enterprise AI platforms.
  • Ensure AI solutions are scalable, secure, maintainable, and aligned with business objectives.
  • Review and approve solution architectures, technical designs, and implementation plans.
AI Governance & Responsible AI
  • Establish and maintain AI governance frameworks, model lifecycle management processes, and responsible AI practices.
  • Oversee model evaluation, monitoring, tracing, and observability using platforms such as Arize AI Phoenix, Azure AI Foundry Evaluation, and similar tools.
  • Ensure compliance with organizational policies, regulatory requirements, privacy standards, and model risk management practices.
  • Lead AI risk assessments, model reviews, and governance committee discussions.
Required Skills
  • Strong understanding of Generative AI, Large Language Models (LLMs), Workflow Agents, RAG Architectures, Semantic Search, and AI-to-SQL solutions.
  • Proven experience designing and deploying scalable cloud-native solutions using at least one key data or AI platform, such as Microsoft Azure AI Foundry, Azure OpenAI, Snowflake, Microsoft Fabric, or Databricks
  • Experience designing and delivering enterprise AI platforms and AI-enabled business applications.
  • Knowledge of vector databases including PgVector, Azure AI Search, or similar technologies.
  • Experience implementing AI observability, evaluation, tracing, and monitoring solutions using Arize AI Phoenix, LangSmith, Azure AI Foundry Evaluation, or equivalent tools.
  • Strong understanding of data governance, AI governance, model risk management, and responsible AI principles.
  • Experience with enterprise integration patterns, APIs, microservices, and modern software architecture.
  • Strong project management and Agile delivery experience.
  • Excellent communication, presentation, stakeholder management, and consulting skills.
Education and Experience
  • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Mathematics, or a related field is required.
  • Master's degree in a related discipline is preferred.
  • 8+ years of experience in software engineering, data engineering, analytics, AI/ML, or related technology disciplines.
  • Minimum of 3โ€“5 years of experience leading AI, Data Science, Analytics, or Data Engineering teams.
  • Demonstrated experience delivering enterprise-scale AI or advanced analytics initiatives.
  • Experience within financial services, banking, credit unions, or highly regulated industries is highly preferred.
Preferred Qualifications
  • Experience leading implementation of AI Governance Frameworks and Responsible AI programs.
  • Experience with Azure AI Foundry Agent Service, workflow-based AI agents, and enterprise AI architectures.
  • Experience with intelligent document processing solutions using Azure AI Document Intelligence.
  • Certifications in Microsoft Azure, AI Engineering, Data Engineering, or related technologies.
  • Familiarity with regulatory frameworks impacting AI adoption in financial services.
  • Strategic thinking and business acumen.
  • Strong leadership and team-building capabilities.
  • Ability to align technology investments with business objectives.
  • Excellent communication and executive presentation skills.
  • Strong analytical and problem-solving abilities.
  • Ability to manage multiple priorities and complex stakeholder relationships.
  • Passion for innovation, continuous learning, and emerging AI technologies.
  • Proven ability to drive organizational change and AI adoption initiatives.
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