Co-op - Machine Learning Engineer (Analyst) - Lendbuzz

Job Title: Co-op - Machine Learning Engineer (Analyst)
Job Location: Boston, MA
Job Listing URL: https://jobs.lever.co/lendbuzz/57e868e9-22da-430d-adc7-b53038db6aac
Job Description: 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 seeking a Machine Learning Analyst to enable data-driven decision-making through the development and evaluation of machine learning models and analytical solutions. In this role, you will collaborate with data scientists and business teams to extract insights from complex datasets, improve model performance, and turn analytical results into actionable strategies. This position combines hands-on data analysis with a strong foundation in machine learning and practical business understanding. This is a full time (40 hours) co-op running from January to August, and you will be expected to be in our Boston office 3-4 times a week.
Key Responsibilities:
Analyze large datasets to uncover patterns, trends, and insights that inform model development and business strategy
Support the design, testing, and validation of machine learning models in collaboration with data science teams
Monitor and tune model performance to maintain accuracy, reliability, and business relevance
Communicate analytical findings and model behavior clearly to both technical and non-technical stakeholders
Requirements:
Bachelor’s degree in Computer Science or a related field; Master’s preferred
Coursework or experience in Data Structures, Algorithms, Linear Algebra, Probability, and core Machine Learning/AI concepts
Proficiency in Python and its data analysis libraries (e.g., NumPy, pandas, scikit-learn)
Strong understanding of computer science fundamentals and machine learning principles
Familiarity with Linux fundamentals is a plus
A graduation date of December 2026 or later
Be able to be in the office 3 times a week (hybrid)
Be able to work full time (40 hours a week) during the co-op (January-August 2026)
Interview Process:
Candidates will be assessed on their understanding of coursework, coding ability, probability, machine learning, and Linux basics