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Lendbuzz

Auto loans via data-driven credit assessment

Machine Learning Scientist - Financial Scoring

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBoston, MA, USA$170k - $200k /yr

About the Job

Requirements

  • A Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
  • At least 2 years of relevant industry or postdoctoral experience.
  • A solid understanding of computer science fundamentals, including data structures, algorithms, and object-oriented programming.
  • A deep understanding of machine learning models and algorithms.
  • A 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, PyTorch, and scikit-learn.

Responsibilities

  • Build machine learning and deep learning models based on financial and other modalities, including text.
  • Collaborate closely with cross-functional teams to integrate machine learning models into production systems.
  • Conduct extensive analysis to understand 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 to ensure high-quality, reliable machine learning model releases.
  • Stay updated with advancements in machine learning and related technologies to continuously improve solutions.

About the Company

Lendbuzz

Auto loans via data-driven credit assessment

Lendbuzz provides auto loans in the U.S., focusing on international students and professionals with limited U.S. credit history. Borrowers apply online; Lendbuzz uses data analytics and machine learning to assess creditworthiness beyond traditional credit scores, then coordinates with the dealership to complete the loan. Unlike traditional lenders, it uses a broader set of data to determine eligibility and rates, serving an underserved niche with an end-to-end online process. Its goal is to expand access to auto financing for international students and recent immigrants by applying data-driven credit assessments.

Company size
201-500
Company stage
N/A
Total funding
$3.1B
Headquarters
Boston, MA
Founded
2015

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