Location: Remote (US)   |   Full-Time
Data Science AI Machine Learning Credit Risk Fintech Startup Cashflow Analytics Python SQL Data Science 
Pavefi.com is a rapidly growing startup revolutionizing financial access for 100M+ underserved consumers and small businesses through AI-powered Cashflow Analytics and Scores. Backed by Better Tomorrow, Bessemer, 8VC, and other top funds and angels from Coinbase, Chime, SoFi, CashApp, and Plaid.

We’re hiring a Data Scientist to ship models that will redefine the US credit system, making it fair and inclusive.

Responsibilities:
*   Develop, implement, and deploy cutting-edge machine learning models for credit risk assessment and cashflow analysis.
*   Analyze complex financial datasets to identify patterns, generate insights, and inform model development.
*   Collaborate closely with product and engineering teams to integrate models into Pavefi's platform.
*   Monitor model performance in production and iterate based on results and changing data patterns.
*   Contribute to the overall data science strategy and roadmap.

Technical Skills & Qualifications:
*   Proven experience building and deploying machine learning models in a production environment.
*   Strong understanding of statistical modeling, machine learning algorithms, and data analysis techniques.
*   Proficiency in programming languages commonly used in data science, such as Python (including libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
*   Experience with data processing and database technologies (SQL, NoSQL).
*   Familiarity with cloud platforms (AWS, GCP, Azure) is a plus.
*   Experience in fintech or credit risk modeling is highly desirable.

Ideal Candidate:
*   Passionate about financial inclusion and using AI/ML for positive social impact.
*   Eager to work in a fast-paced, high-growth startup environment.
*   Strong analytical and problem-solving skills.
*   Excellent communication and collaboration abilities.
*   MSc or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
Post Date: May 26, 2025