ZipRecruiter

Log In

2

Remote Credit Risk Modeling Jobs in Norfolk, VA (NOW HIRING)

Alutiiq, LLC

Operations Manager

Chesapeake, VA · On-site +1

$160K - $190K/yr

Taxable Entity ALUTIIQ OPERATIONS SERVICES LLC Job Title Operations Manager Location VA Remote ... Design, implement, and continuously improve operational strategies, staffing models, and resource ...

USAA

Actuarial Analyst I

Chesapeake, VA · On-site +1

$103.45K - $197.73K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... modeling, catastrophe risk, claims analytics, product management, etc.) to complete unstructured ...

USAA

Actuary

Chesapeake, VA · On-site +1

$127.31K - $243.34K/yr

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... models and interprets and communicates results to support critical business activities, while ...

Sentara

CARDIOLOGY PRACTICE MANAGER II

Norfolk, VA · On-site +1

M-F (Day Shift) Overview The Practice Manager II partners with clinical leadership in dyad model to ... budget, risk management, and compliance with organizational and ambulatory care policies ...

Fugro

Hydrographic Sales Manager - Marine

Norfolk, VA · On-site +1

$93.50K - $149.60K/yr

This role can be fully remote The salary range for this role is $93,500.00 - 149,600.00 USD Job ... risk. * Work closely with the Director of Hydrography and Commercial Team to identify market ...

Fugro

Hydrographic Sales Manager - Marine

Norfolk, VA · On-site +1

$93.50K - $149.60K/yr

This role can be fully remote The salary range for this role is $93,500.00 - 149,600.00 USD Job ... risk. * Work closely with the Director of Hydrography and Commercial Team to identify market ...

next page

Showing results 1-20

People also search for

All JobsRemote Credit Risk Modeling JobsRemote Credit Risk Modeling Jobs in Norfolk, VA

Remote Credit Risk Modeling information

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

To thrive as a Remote Credit Risk Modeler, you need a strong background in statistics, data analysis, and financial risk assessment, typically supported by a degree in mathematics, finance, or a related field. Familiarity with statistical modeling tools such as SAS, R, Python, and experience with credit risk platforms or regulatory frameworks like Basel II/III are highly valued. Excellent problem-solving skills, attention to detail, and effective communication are crucial for interpreting complex data and collaborating with remote teams. These skills ensure accurate risk assessments, regulatory compliance, and sound decision-making in credit portfolios.

How does a remote Credit Risk Modeling professional typically collaborate with cross-functional teams?

As a remote Credit Risk Modeling professional, collaboration with cross-functional teams—such as data analysts, IT specialists, and business stakeholders—is usually facilitated through virtual meetings, shared project management tools, and version-controlled code repositories. Clear communication and regular updates are essential, as you'll often need to translate complex modeling outcomes into actionable insights for non-technical colleagues. Building strong relationships remotely can be a challenge, but utilizing video calls and collaborative documentation helps ensure alignment on project goals and timelines.

What is remote credit risk modeling?

Remote credit risk modeling involves analyzing and predicting the likelihood that borrowers will default on their loans, all while working from a location outside of a traditional office setting. Professionals in this role use statistical techniques and data analysis tools to assess creditworthiness and help financial institutions minimize risk. They often collaborate with teams virtually, utilizing secure platforms to access data and build predictive models. This remote setup allows for flexibility and efficiency while still upholding high standards of data security and accuracy.

What is the difference between Remote Credit Risk Modeling vs Remote Credit Analyst?

AspectRemote Credit Risk ModelingRemote Credit Analyst
Required CredentialsDegree in Finance, Economics, or related field; certifications like CFA or FRM beneficialDegree in Finance, Economics, or related field; certifications like CFA or FRM beneficial
Work EnvironmentDeveloping models, analyzing data, using statistical softwareAssessing creditworthiness, reviewing financial documents, communicating with clients
Industry UsageFinancial institutions, credit bureaus, fintech companiesBanks, lending institutions, credit agencies

Remote Credit Risk Modeling focuses on creating statistical models to predict credit risk, requiring strong analytical skills and technical expertise. Remote Credit Analysts evaluate individual credit applications and assess risk based on financial data. While both roles operate remotely within the finance industry, they differ in daily tasks and skill emphasis, with modeling being more technical and analysis more client-focused.

What are popular job titles related to Remote Credit Risk Modeling jobs in Norfolk, VA? For Remote Credit Risk Modeling jobs in Norfolk, VA, the most frequently searched job titles are:
What job categories do people searching Remote Credit Risk Modeling jobs in Norfolk, VA look for? The top searched job categories for Remote Credit Risk Modeling jobs in Norfolk, VA are:
What cities near Norfolk, VA are hiring for Remote Credit Risk Modeling jobs? Cities near Norfolk, VA with the most Remote Credit Risk Modeling job openings:
Remote Credit Risk Modeling jobs near you
Senior MLOps & Generative AI Engineer - Remote

Senior MLOps & Generative AI Engineer - Remote

Sentara Health

Virginia Beach, VA • Remote

$99.20K - $136.20K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Sentara Health rating

6.8

Company rating: 6.8 out of 10

Based on 379 frontline employees who took The Breakroom Quiz

489th of 864 rated healthcare providers

Job description

City/State
Virginia Beach, VA
Work Shift
First (Days)
Overview:
Sentara is hiring a Senior MLOps & Generative AI Engineer!
This position is fully remote!
Candidates must reside in one of the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming.
Overview
We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence.
This role combines two critical focus areas:
  • MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities.
  • Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks.

As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments.
Key Responsibilities
MLOps Engineering Responsibilities
  • Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management.
  • Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments.
  • Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation.
  • Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads.
  • Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability.
  • Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes.
  • Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment.
  • Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code.
  • Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them.
  • Support enterprise AI governance, compliance, auditability, and model risk management requirements.
  • Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems.

Generative AI Engineering Responsibilities
  • Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies.
  • Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
  • Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability.
  • Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases.
  • Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics.
  • Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments.
  • Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications.
  • Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments.
  • Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows.
  • Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement.
  • Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives.
  • Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data.
  • Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices.

Required Qualifications
  • 5+ years of experience building and deploying production software, ML systems, or AI platforms.
  • 1+ years of hands-on experience building production Generative AI or LLM-based applications.
  • Strong programming skills in Python and experience with software engineering best practices.
  • Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent.
  • Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks.
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies.
  • Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP.
  • Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures.
  • Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure.
  • Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices.
  • Experience building monitoring, observability, and alerting solutions for ML and AI systems.
  • Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations.
  • Experience designing secure, scalable, production-ready AI platforms and services.
  • Strong communication and collaboration skills with the ability to work across technical and business teams.

Preferred Qualifications
  • Previous experience implementing Generative AI and MLOps solutions within healthcare environments.
  • Experience working with EPIC or healthcare interoperability platforms.
  • Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices.
  • Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling.
  • Experience with GPU infrastructure optimization and scalable inference architectures.
  • Familiarity with multi-agent AI systems and autonomous workflows.
  • Experience with event-driven architectures, streaming pipelines, and real-time inference systems.
  • Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies.
  • Experience with enterprise AI platform architecture and internal developer platforms.
  • Prior experience mentoring engineers and leading technical initiatives.

Education
  • 5+ years of relevant experience with a degree (Required)

or
  • 7+ years of relevant experience without a degree (Required)
  • Experience in lieu of Bachelor's Degree.

Certification/Licensure
  • No specific certification or licensure requirements

Experience
  • 5 to 7 years of relevant experience

We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities.
Keywords: Talroo-IT, MLOps, Gen AI, LLM, AWS, Azure, GCP, AI/ML, Python, PyTorch, Hugging Face Transformers, TensorFlow, RAG, EPIC, HIPAA, AI Governance
Benefits: Caring For Your Family and Your Career
• Medical, Dental, Vision plans
• Adoption, Fertility and Surrogacy Reimbursement up to $10,000
• Paid Time Off and Sick Leave
• Paid Parental & Family Caregiver Leave
• Emergency Backup Care
• Long-Term, Short-Term Disability, and Critical Illness plans
• Life Insurance
• 401k/403B with Employer Match
• Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education
• Student Debt Pay Down - $10,000
• Reimbursement for certifications and free access to complete CEUs and professional development
•Pet Insurance
•Legal Resources Plan
•Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met.
Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves.
In support of our mission “to improve health every day,” this is a tobacco-free environment.
For positions that are available as remote work, Sentara Health employs associates in the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

What Sentara Health employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply