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Credit Risk Data Science Jobs in Florida (NOW HIRING)

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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 Florida? For Credit Risk Data Science jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Credit Risk Data Science jobs in Florida look for? The top searched job categories for Credit Risk Data Science jobs in Florida are:
What cities in Florida are hiring for Credit Risk Data Science jobs? Cities in Florida with the most Credit Risk Data Science job openings:
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Infographic showing various Credit Risk Data Science job openings in Florida as of May 2026, with employment types broken down into 2% As Needed, 81% Full Time, and 17% Part Time. Highlights an 95% Physical, 3% Hybrid, and 2% Remote job distribution.
VP of Credit & Business Intelligence (FL)

VP of Credit & Business Intelligence (FL)

One Park Financial

Miami, FL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago

Job description

About One Park Financial

One Park Financial, a leading provider of financing solutions for small and mid-sized businesses, has been consistently recognized as a top workplace for seven consecutive years, earning both the Best Place to Work and Sun Sentinel's Top Places to Work awards. As a fast-paced and innovative financial services company, we take immense pride in disrupting the industry and positively impacting the lives of business owners nationwide. At One Park Financial, excellence and results are celebrated, and your skills and passion will be recognized and rewarded, providing opportunities for both professional and personal growth.

About the VP of Credit & Business Intelligence

Reporting directly to the SVP of Credit & Analytics, the successful candidate will oversee the Credit Policy & Analytics function for small business financing and emerging embedded finance products. This pivotal role aims to empower small businesses by managing the risk appetite through advanced decisioning models, growth strategies, reporting, and analytics vital to the organization.

Requirements

Job Responsibilities

  • Own Credit Policy & Analytics across the organization – Credit Origination, Account Management, Portfolio monitoring, Collections and Loss/Growth Forecasting.
  • Lead development, validation and implementation of advanced AI/ML models and strategies to expand small business access to finance, taking intelligent risks.
  • Develop and maintain the key portfolio KPIs and inventory of periodic analysis to continuously identify risk and growth opportunities.
  • Support effective challenge of Business Operations through Data & Data Science based Business Intelligence rhythms.
  • Partner with Product, Engineering and Operations to productionize strategies in decision engines, while ensuring data quality, monitoring and controls.
  • Leverage Open Banking (Plaid), Credit (Commercial & Personal), Business Identity, Fraud and validation sources to evaluate improvements in our Credit strategy and merchant experience.
  • Identify areas to reshape user flows, reduce customer friction and optimize the credit funnel.
  • Manage Analytics infrastructure needs for proactive highlighting of issues that need to be addressed and prioritized in the organization.
  • Manage Executive discussions on Analytics prioritization for the most pressing business needs.
  • Coach, Mentor and Develop the Analytics team to turn into effective Credit & Business Intelligence champions and credit policy owners.

Job Requirements

  • 8-10 years of credit and/or analytics experience at Fintechs or Credit institutions, with 3+ years of direct merchant / SMB risk experience preferred.
  • Deep knowledge of underwriting using bank & cash-flow analysis, bureau & alternate data, bureaus etc. with a focus on unsecured credit risk.
  • 5+ years of leading teams (data science, analytics, risk policy) and scaling analytics functions at a growing organization.
  • Proven track record of implementing business intelligence-based optimization strategies (reporting & alerting) with P&L impact.
  • Fluency in SQL and Python or R; experience with BI tools (PowerBI/Tableau) and cloud data platforms (Snowflake/AWS/Databricks).
  • Outstanding leadership, communication, and interpersonal skills, with the innate ability to inspire and motivate a team.
  • Bachelors in a quantitative field; advanced MS/PhD qualifications are a plus.

Benefits

  • Dental Insurance
  • Health insurance
  • Vision insurance
  • Paid time off
  • 401k with Match
  • Company Paid ID Protection
  • Company Paid Life Insurance