Credit Strategy Data Scientist

globalplacementfirm; San Jose (CA); Remote; USD 120,000 - 150,000; Full time

Job summary

globalplacementfirm is seeking a Credit Strategy Data Scientist to join its Credit Risk Strategy team. This remote, 12-month contract role focuses on building data-driven credit solutions and risk controls to support responsible growth.

You will design rules, analyze loss trends, and develop dashboards (Tableau) for executives, working with wide datasets and cross-functional partners in fintech/payments. Strong SQL, Python, and communication skills are essential.

Qualifications

• Bachelor's degree in CS/Engineering/Math/Stats or related field.
• 2+ years in risk analytics, data science, or data analysis, preferably fintech/payments.
• Proficiency in SQL, Python, and Excel with core data science libraries.

Responsibilities

• Design and implement data-driven rules to detect and mitigate credit losses.
• Investigate complex and high-impact risk cases and identify root causes.
• Set and refine credit risk strategies across various risk categories.
• Collaborate with product and engineering teams to enhance risk control capabilities.
• Lead the development of dashboards, visualizations, and reports to track credit KPIs.
• Present data-backed recommendations to stakeholders and executives.
• Use large-scale datasets to uncover patterns and drive risk optimization.
• Work with RaaS platforms to analyze loss trends and apply strategic adjustments.

Skills

SQL

Python

Excel

Data analysis

Tableau

Communication

Education

Bachelor's degree

Tools

AWS

Job description

Credit Strategy Data Scientist

Location: Remote (U.S.-based candidates only) - 12 month contract
Full-Time | MidSenior Level | No Visa Sponsorship or Relocation

Overview

A fast-growing financial services organization is seeking a Credit Strategy Data Scientist to join its high-performing Credit Risk Strategy team. This is an exciting opportunity for a data-savvy professional with fintech or payments industry experience to help drive business-critical decisions through advanced analytics, predictive modeling, and risk mitigation strategies.

You will work on end-to-end development of data-driven credit solutionspartnering closely with cross-functional stakeholders to design, execute, and refine credit strategies that support responsible growth and customer success.

What Youll Do

• Design and implement data-driven rules to detect and mitigate credit

  losses
• Investigate complex and high-impact risk cases and identify root causes
• Set and refine credit risk strategies across various risk categories
• Collaborate with product and engineering teams to enhance risk control capabilities
• Lead the development of dashboards, visualizations, and reports to track credit KPIs

• Present data-backed recommendations to stakeholders and executives

• Use large-scale datasets to uncover patterns and drive risk optimization
• Work with RaaS platforms to analyze loss trends and apply strategic adjustments

Must-Have Qualifications

• Bachelors degree in Computer Science, Engineering, Mathematics, Statistics, Data Mining, or a related field (or equivalent practical experience)
• 2+ years of hands-on experience in risk analytics, data science, or data analysispreferably within fintech or online payments
• Proficiency in SQL, Python, and Excel, including core data science libraries
• Proven ability to work with large datasets and derive actionable insights
• Experience developing and communicating dashboards and visualizations (e.g. Tableau)
• Strong communication skills and ability to translate complex analysis to diverse audiences

• Demonstrated data-driven decision-making and solution development

Preferred Skills & Experience

• Experience applying data science to credit risk and loss mitigation problems
• Familiarity with AWS, payment rule systems, or credit product lifecycles
• Strong project management skills and ability to drive analytics from concept to execution
• Comfortable working in fast-paced, ambiguous environments with shifting priorities

Expected Outcomes (6-12 Months)

• Design and deployment of credit strategies based on emerging loss trends
• Creation of performance dashboards and tools to monitor KPIs and credit risk health
• Collaboration with product and engineering teams to implement real-time credit decisioning
• Delivery of presentations and reports to support strategic decisions at all levels

Key Competencies

• Data Analytics & Visualization

• Credit Rule Development

• Strategic Communication

• Cross-Functional Collaboration

• Project Ownership & Execution

Interview Process

• At-home screening assignment

• Technical interview with senior team member

• Final panel interview with hiring manager and team

Team Size: 5 members
Work Style: Close collaboration with senior data scientists initially, with room for independent ownership over time.
Focus Area: Reporting, visualization, and strategy design

This is a high-impact role at the intersection of data science, risk management, and business strategyperfect for professionals passionate about leveraging data to drive innovation in financial services.