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Credit Risk Data Science Jobs in Miami, FL (NOW HIRING)

Provides research into industry trends and evaluation of market data impacting prospective or ... Working knowledge of applicable industry laws and regulations required to review credit risk. Solid ...

Design and implement advanced ML models and statistical methods to optimize forecasting, risk ... A Master's degree in Data Science, Machine Learning, Statistics, or a related field, or nine (9) ...

Senior Credit Analyst

Miami, FL · On-site

$100 - $125/hr

Provides research into industry trends and evaluation of market data impacting prospective or ... Working knowledge of applicable industry laws and regulations required to review credit risk. Solid ...

Mathematics, statistics, computer science, data science or field directly related to the position ... You will receive credit for all qualifying experience, including volunteer experience. To qualify ...

Join our team and use advanced data, AI, and emerging technologies with industry insights to help ... Credit Risk, Liquidity Risk, Market Risk, Capital Management/Stress Testing * Knowledge of ...

Experience building credit or risk models for Financial Services, Lending, or Insurance. * Experience in validating models to identify ongoing improvements. * Rock Solid data science skillset:

Experience building credit or risk models for Financial Services, Lending, or Insurance. * Experience in validating models to identify ongoing improvements. * Rock Solid data science skillset:

Experience building credit or risk models for Financial Services, Lending, or Insurance. * Experience in validating models to identify ongoing improvements. * Rock Solid data science skillset:

Showing results 41-60

Credit Risk Data Science information

See Miami, FL salary details

$35.4K

$108.9K

$188.9K

How much do credit risk data science jobs pay per year?

As of Sep 9, 2026, the average yearly pay for credit risk data science in Miami, FL is $108,921.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,900.00 and $134,400.00 per year, depending on experience, location, and employer.

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 Miami, FL?

For Credit Risk Data Science jobs in Miami, FL, the most frequently searched job titles are:

What job categories do people searching Credit Risk Data Science jobs in Miami, FL look for?

The top searched job categories for Credit Risk Data Science jobs in Miami, FL are:

What cities near Miami, FL are hiring for Credit Risk Data Science jobs?

Cities near Miami, FL with the most Credit Risk Data Science job openings:

Head of Data Science - Document Verification & Biometrics

Miami, FL • On-site

Socure
Software Development • 501 - 1,000 employees

Full-time

Re-posted 2 days ago


Job description

Job Summary:
Socure is building the identity trust infrastructure for the digital economy, and they are seeking an exceptional leader to drive AI-powered Document Verification and Biometrics solutions. This role involves owning the data science strategy and execution, leading a team of data scientists, and advancing fraud detection capabilities.
Responsibilities:
• Own and define the data science vision for Document Verification, Biometrics, and Reusable ID, delivering step-function improvements in accuracy, speed, and user experience.
• Lead and scale a high-performing team of data scientists and applied researchers, setting a high standard for execution, innovation, and accountability.
• Architect and deploy state-of-the-art computer vision and multimodal systems, including vision-language models (VLMs), for document understanding, face matching, liveness detection, and identity verification.
• Drive the development of domain-specific foundation models tailored to identity, documents, and biometrics, leveraging large-scale proprietary datasets.
• Lead the transition to agentic systems, building intelligent agents that can reason over document and biometric signals, automate verification workflows, and adapt dynamically to new fraud patterns.
• Advance fraud and attack detection capabilities, including deepfake detection, presentation attack detection, and counterfeit document detection.
• Design and implement secure and robust systems resilient to emerging threats such as prompt injection and adversarial attacks on multimodal and agent-based systems.
• Leverage vector databases and embedding systems to power similarity search, identity linking, and reusable identity experiences.
• Partner closely with Product, Engineering, and Risk teams to deliver scalable, production-grade solutions that meet both business and regulatory requirements.
• Drive rapid experimentation and deployment, balancing innovation with reliability, explainability, and compliance.
• Own customer communication and stakeholder management, serving as a trusted technical leader in engagements with customers, partners, and internal stakeholders; clearly articulate model behavior, agentic systems, performance trade-offs, and roadmap decisions while building strong, long-term relationships.
• Represent Socure externally as a thought leader in biometrics, document AI, and fraud prevention.
Qualifications:
Required:
• Advanced degree (MS/PhD preferred) in Computer Science, Electrical Engineering, Machine Learning, or a related field.
• 10+ years of experience in data science, machine learning, or applied AI, with a strong track record of building and deploying production systems.
• Deep expertise in computer vision and multimodal AI, including experience with vision-language models (VLMs).
• Proven experience building domain-specific foundation models or large-scale representation learning systems.
• Strong understanding of biometric systems, including face recognition, liveness detection, and anti-spoofing techniques.
• Experience detecting and mitigating deepfakes, presentation attacks, and counterfeit documents.
• Strong understanding of agentic system design, including agent skills, orchestration/harness frameworks, and real-world deployment of autonomous or human-in-the-loop agents.
• Experience with vector databases and embedding-based retrieval systems.
• Strong awareness of emerging attack vectors, including prompt injection, adversarial inputs, and model exploitation techniques.
• Proven ability to lead and scale high-performing teams while delivering under ambiguity and tight timelines.
• Proficiency in Python and modern ML frameworks (e.g., PyTorch).
• Proven ability to engage with customers and external stakeholders, clearly explaining complex AI systems, trade-offs, and outcomes to both technical and non-technical audiences.
Preferred:
• MS/PhD preferred in Computer Science, Electrical Engineering, Machine Learning, or a related field.
• Experience representing organizations in customer-facing discussions, executive briefings, or public speaking engagements is strongly preferred.
Company:
Socure provides digital identity verification, fraud prevention, and regulatory compliance software through an AI-driven platform. Founded in 2012, the company is headquartered in Incline Village, USA, with a team of 501-1000 employees. The company is currently Late Stage.