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Credit Risk Data Science Jobs in Iowa (NOW HIRING)

AI Data Engineer - Senior Consultant

Des Moines, IA · On-site

$103.40K - $140.50K/yr

... risk) and document decisions. • 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security. • 4+ years of experience with treat testing ...

AI Data Engineer - Senior Consultant

Des Moines, IA · Hybrid

$102K - $140K/yr

... vs. risk) and document decisions. * 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security. * 4+ years of experience with treat testing ...

AI Data Engineer - Senior Consultant

Davenport, IA · Hybrid

$99.10K - $136.10K/yr

... vs. risk) and document decisions. * 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security. * 4+ years of experience with treat testing ...

... risk rating recommendations, trend analysis, and identifying the credit's strength and weaknesses. Do you enjoy working with financial data and learning what makes businesses grow? Do you enjoy ...

... of risk and security awareness.* 10) Establishes a good image for the Bank by being active and ... Reasoning Ability to define problems, collect data, establish facts, and draw valid conclusions.

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Credit Risk Data Science information

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.

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 popular job titles related to Credit Risk Data Science jobs in Iowa? For Credit Risk Data Science jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Iowa look for? The top searched job categories for Credit Risk Data Science jobs in Iowa are:
AI Data Engineer - Senior Consultant

AI Data Engineer - Senior Consultant

Deloitte

Des Moines, IA • On-site

$103.40K - $140.50K/yr

Full-time

Posted 11 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

59th of 138 rated financial services


Job description

Job Summary:
Deloitte's Human Capital team is seeking an AI Engineer Senior Consultant to build and operate the data and AI foundations that enhance Human Capital AI products and analytics. This hands-on role involves designing and delivering secure, scalable AI solutions in collaboration with various teams to support model training and real-time inference.
Responsibilities:
• Partner with the Lead AI Solutions Architect and AI Data Engineer to translate Human Capital product needs into secure, scalable technical designs and delivered solutions (APIs, services, pipelines, containers/serverless) meeting availability, performance, and security expectations.
• Build and operationalize LLM-enabled capabilities (e.g., copilots, HR knowledge assistants, summarization, policy Q&A) using Claude/GPT(Codex)/Gemini, including secure endpoints, tool/function calling, and reusable prompt/context patterns.
• Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector/hybrid search, and retrieval/evaluation telemetry.
• Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills).
• Implement safety, privacy, and access controls (PII handling, prompt-injection defenses, content filtering, policy-based access) with security and risk stakeholders.
• Establish data/model reliability and cost-performance discipline (data quality, schema evolution, lineage/metadata, monitoring; right-sizing, query tuning, LLM token/cost telemetry).
• Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing, observability, incident response); support design reviews, deployment readiness, and runbooks.
Qualifications:
Required:
• Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science)
• 4+ years building and delivering LLM/GenAI solutions with Claude/GPT(Codex)/Gemini-class models, including prompt/context design, tool/function calling, evaluation, and production integration.
• 4+ years implementing RAG/retrieval (document processing, embeddings, vector/hybrid search) with enterprise governance controls.
• 4+ years of modern data & AI engineering, including data modeling, batch/streaming pipelines, structured/unstructured processing, and feature engineering/serving fundamentals.
• 4+ years building production, real-time inference services (API design, latency/performance, reliability patterns).
• 4+ years leading platform/integration engineering across enterprise systems; strong API/integration experience (REST, GraphQL, event-driven, microservices, middleware).
• 4+ years DevOps/DevSecOps experience (CI/CD, IaC such as Terraform/CloudFormation, Docker/Kubernetes, observability/monitoring).
• 4+ years leading security/compliance efforts; familiarity with enterprise security controls (IAM, encryption, secrets, audit logging) and data/privacy (PII, retention, access controls); SOC 2/GDPR/HIPAA exposure a plus.
• Ability to travel 0-25%, on average, based on client and project needs.
• Limited immigration sponsorship may be available
Preferred:
• Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML).
• 4+ years of experience with Human Capital platforms and integrations (e.g., Workday, SAP SuccessFactors, Oracle HCM, Salesforce) and HR data domains.
• 4+ years of experience operationalizing LLMOps/MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management).
• 4+ years of cloud experience on AWS/Azure/GCP (one or more), including managed data platforms and scalable compute patterns.
• 4+ years of experience with structured problem solving, translating business needs into requirements, acceptance criteria, and shippable increments.
• 4+ years of experience with stakeholder communication: ability to explain AI/GenAI trade-offs (quality vs. latency vs. cost vs. risk) and document decisions.
• 4+ years of experience collaborating across product, data science/ML, data engineering, platform, and security.
• 4+ years of experience with treat testing, monitoring, and operational readiness as core responsibilities.
• 4+ years of experience with ethics and privacy awareness being able to recognize consent/PII/bias boundaries and escalate appropriately.
Company:
Deloitte is a business consulting company that offers audit, consulting, financial advisory, and tax services. Founded in 1845, the company is headquartered in London, GBR, with a team of 10001+ employees. The company is currently Late Stage.

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