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Internship Quantitative Risk Modeler Jobs in Union City, GA

Intuit

Staff AI Scientist

Atlanta, GA · On-site

In this role, you'll develop cutting-edge credit risk AI/ML models for new lending products. Join a ... quantitative discipline * 4+ years of work experience in AI Science / Machine Learning and related ...

ClarityPay

Head of Modeling

Atlanta, GA · On-site

$150 - $200/hr

Merchant‑and channel‑level risk -- modeling and monitoring risk that originates from the ... Advanced degree in a quantitative field (statistics, economics, math, computer science, or similar)

YouLend Limited

Senior Credit Risk Analyst

Atlanta, GA · On-site

$110 - $140/hr

Proven understanding of credit underwriting principles, data science model application, risk appetite frameworks, and portfolio risk management. * Outstanding quantitative and deductive reasoning ...

New

YouLend

Senior Credit Risk Analyst

Atlanta, GA · On-site

Proven understanding of credit underwriting principles, data science model application, risk appetite frameworks, and portfolio risk management. * Outstanding quantitative and deductive reasoning ...

YouLend

Senior Credit Risk Analyst

Atlanta, GA · On-site

$90 - $130/hr

Proven understanding of credit underwriting principles, data science model application, risk appetite frameworks, and portfolio risk management. * Outstanding quantitative and deductive reasoning ...

Deloitte

Financial Risk Senior Consultant

Atlanta, GA · On-site

$112K/yr

... g., Quant MS, MBA, FRM, CFA, CRCM, CPA, PMP). * Expertise in one or more Financial Risk domains: * Credit Risk: Underwriting and portfolio credit risk across products (e.g., PD/LGD/EAD modeling ...

Deloitte

Financial Risk Senior Consultant

Atlanta, GA · On-site

$112K/yr

... g., Quant MS, MBA, FRM, CFA, CRCM, CPA, PMP). * Expertise in one or more Financial Risk domains: * Credit Risk: Underwriting and portfolio credit risk across products (e.g., PD/LGD/EAD modeling ...

Carmax

Director, Credit Risk & Analytics

Atlanta, GA · On-site

Owning P&L responsibilities by developing forecast models and successfully steering the business to ... Advanced degree in a quantitative discipline (engineering, math, statistics, operations research ...

AIG

AI Model Validation Lead, GenAI

Atlanta, GA · On-site

... quantitative and qualitative assessments. • Review model development documentation, code, and ... model risk management, or related roles. • Expertise in supervised and unsupervised learning ...

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Internship Quantitative Risk Modeler information

What is the difference between Internship Quantitative Risk Modeler vs Quantitative Risk Analyst?

AspectInternship Quantitative Risk ModelerQuantitative Risk Analyst
CredentialsTypically pursuing or recent graduate in finance, mathematics, or related fieldsOften requires a degree in finance, economics, or quantitative disciplines; certifications like FRM or CFA are common
Work EnvironmentInternship setting, learning-focused, supervised by senior staffFull-time professional role, responsible for risk assessment and modeling
Employer & Industry UsageUsed in banks, asset management firms, and financial institutions for training and entry-level rolesCommon in financial services, banking, and investment firms for ongoing risk management

The Internship Quantitative Risk Modeler is an entry-level, learning-focused role typically held by students or recent graduates, whereas the Quantitative Risk Analyst is a full-time professional responsible for analyzing and managing risk using quantitative models. The internship provides foundational experience, while the analyst role involves ongoing risk assessment and decision-making.

What cities near Union City, GA are hiring for Internship Quantitative Risk Modeler jobs?

Cities near Union City, GA with the most Internship Quantitative Risk Modeler job openings:

Internship Quantitative Risk Modeler jobs near you

Staff AI Scientist

Intuit

Atlanta, GA • On-site

Full-time

Re-posted 26 days ago

Intuit rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

107th of 245 rated software companies

Job description

Company Overview
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Job Description
Intuit's Consumer Group, including TurboTax and Credit Karma, empowers millions of individuals to take control of their finances. TurboTax simplifies tax preparation and enables our customers to file with confidence. By harnessing the power of data and artificial intelligence (AI), we continuously innovate and evolve our consumer offerings to deliver even greater value.
As we expand into Consumer Lending within the Consumer Group, Intu it Credit Karma is looking for an innovative , experienced, and hands-on Staff AI Scientist to join our Consumer Risk AI Science team. In this role, you'll develop cutting-edge credit risk AI/ML models for new lending products. Join a collaborative and inventive team of AI scientists and machine learning engineers where your work will have a direct impact on hundreds of thousands of customers.
Responsibilities
What you'll do:
  • Contribute to the credit risk AI science initiatives for the new and evolving Money product offerings focusing on the lending domain, including complete hands-on ownership of the model lifecycle, sharing ownership of success and key results at the program-level, and driving the data strategy across all involved teams.
    • Design, build, deploy, evaluate, defend, and monitor machine learning models to predict credit risk for various short-term lending products (e.g., tax refund advances, BNPL, installment loans, line of credit, and early wage access)
    • Collaborate with credit policy, product and fraud risk teams to ensure models align with business goals and product offering to drive actionable lending decisions
    • Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and both commercially available and proprietary Machine Learning and AI infrastructures
    • Deploy models in a production environment in collaboration with other AI scientists and machine learning enginers
    • Ensure model fairness, interpretability, and compliance with FCRA, ECOA, and other relevant regulatory frameworks
  • Build next-generation credit risk models for short-term lending products using advanced deep learning techniques (e.g., transformers, sequence models, and representation/embedding learning on tabular and time-series financial data)
  • Build and improve transaction categorization models that power cash flow underwriting and credit risk models for thin-file and sub-prime consumers.
  • Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve efficiency and effectiveness of AI science solutions.
  • Research and implement practical and creative machine learning and statistical approaches suitable for our fast-paced, growing environment.
  • Design, build, and deploy AI agents and orchestration workflows powered by Agentic AI to automate the end-to-end model development lifecycle-data exploration, feature engineering, data validation, model training, evaluation, and monitoring-accelerating team velocity and productivity.

Qualifications
Minimum Basic Requirements:
  • Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics or a related quantitative discipline
  • 4+ years of work experience in AI Science / Machine Learning and related areas
  • Authoritative knowledge of Python and SQL
  • Relevant work experience in fintech credit risk, with deep understanding of payment systems, money movement products, banking, and lending
  • Experience leveraging credit bureau, tax and cash flow data in credit risk model development
  • Deep, hands-on expertise developing , deploying, monitoring and maintaining a variety of machine learning techniques, including but not limited to, deep learning ( transformers, sequence modeling), tree-based models, reinforcement learning, clustering, time series, causal analysis, and natural language processing.
  • Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation
  • Ability to quickly develop a deep statistical understanding of large, complex datasets
  • Expertise in designing and building efficient and reusable data pipelines and framework for machine learning models
  • Strong business problem solving, communication and collaboration skills
  • Ambitious, results oriented, hardworking, team player, innovator and creative thinker
  • Proven experience defining and driving end-to-end modeling frameworks, methodologies, or best practices across multiple product teams or domains.
  • Demonstrated ability to evaluate and integrate emerging AI/ML technologies, contributing to the company's external technical visibility and innovation agenda.

Preferred Qualifications:
  • Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
  • Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow
  • Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring, and version control
  • Experience with experimentation design and analysis, including A/B testing and statistical analysis.
  • Working knowledge of LLMs and AI agents (prompt engineering, RAG, tool calling, agentic workflows) and familiarity with orchestration frameworks (e.g., LangChain, LangGraph) and the Gen AI stack (embeddings, vector databases, fine-tuning).
  • Experience building transaction categorization and cash flow modeling pipelines from bank/aggregator data (e.g., Plaid, Nova Credit, MX, Finicity) for credit risk or underwriting use cases.

Footer
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

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