Data Scientist

About Pave: Pave is a rapidly growing startup revolutionizing financial access for underserved consumers and small businesses through AI-powered Cashflow Analytics and Scores. We help lenders reduce defaults, provide optimal loan amounts, and maximize collections success by leveraging data and machine learning.

About The Role: We are seeking a Data Scientist to ship models that will redefine the US credit system, making it fair and inclusive. You will play a key role in developing machine learning models that assess cashflow-based credit risk, enabling lenders to make better lending decisions for underserved populations.

Key Responsibilities:

• Design and implement machine learning models for credit risk assessment
• Analyze large-scale financial datasets to identify patterns and insights
• Collaborate with engineering teams to deploy models into production
• Continuously evaluate and improve model performance
• Research novel approaches to cashflow-based credit scoring
• Develop features and metrics to monitor model performance in production

Required Skills and Qualifications:

• 3+ years of experience as a Data Scientist
• Strong background in machine learning and statistical modeling
• Proficiency in Python and relevant libraries (scikit-learn, TensorFlow, PyTorch)
• Experience with large-scale data processing and feature engineering
• Understanding of financial concepts and credit risk
• Excellent communication and collaboration skills
• Experience with model deployment and monitoring in production environments

What We Offer:

• Competitive salary and equity
• Opportunity to work on impactful financial technology
• Collaborative and innovative work environment
• Remote-first culture with flexible work arrangements
• Comprehensive benefits package including health insurance and professional development opportunities

Compensation: The estimated pay range for this role is $130,000 - $170,000. This role is eligible for equity participation.