Machine Learning Scientist (Financial Scoring)

At Lendbuzz, we believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, we’ve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking.

We are looking for a talented Machine Learning Scientist who is passionate about delivering impactful solutions and thrives in a dynamic, collaborative environment. The ideal candidate will possess a strong background in software development, excellent data analysis and communication skills, and a deep understanding of machine learning and statistics.

Responsibilities

Build machine learning and deep learning models based on financial and other modalities like images and text Collaborate closely with cross-functional teams to integrate machine learning models seamlessly into production systems Conduct extensive analysis to better understand our continually evolving datasets and validate model performance Design and develop robust, scalable pipelines and services using software engineering best practices Implement end-to-end solutions, including architecture design, business logic, and deployment Drive the adoption of rigorous testing practices, ensuring high-quality, reliable ML model releases Stay updated with advancements in machine learning and related technologies to continuously improve our solutions

Requirements

Ph.D in Computer Science, Statistics, Mathematics or a related field 2+ years of relevant industry or postdoc experience Solid understanding of computer science fundamentals, including data structures and algorithms and object oriented programming Deep understanding of machine learning models and algorithms Deep understanding of probability and statistics Strong data analysis skills and experience working with messy real world data Proficiency in python and familiarity with commonly used machine learning libraries such as numpy, pandas, torch, and scikit-learn Excellent communication skills