Machine Learning Scientist, Financial Scoring

🕒 March 27

🏢🏡 Boston – Hybrid

💵 $150k - $190k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

💸 Financial Planning and Analysis (FP&A)

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Lendbuzz

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2015

💸 Finance

💳 Fintech

Finance • Fintech

Lendbuzz is a US-based fintech company that offers auto loans, private-party vehicle financing, and refinancing solutions by evaluating applicants’ broader financial profiles rather than relying solely on traditional credit scores. The company provides a streamlined digital application and verification process for consumers and partners with car dealerships to originate loans quickly and securely; loans are made by Lendbuzz Funding, LLC.

📋 Description

• 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