Machine Learning Scientist (Financial Scoring)

Lendbuzz Inc.
Boston, MA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Data Analysis Business Logic Data Structures Python (Programming Language) Machine Learning NumPy Object-Oriented Software Development Software Engineering Pandas Scikit Learn Information Technology Software Library

Job description

  • Build machine learning and deep learning models based on financial and other modalities like 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

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 deep understanding of machine learning and statistics and a strong background in data analysis, software development, and communication skills., * 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

About the company

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 love collaborating in person, and we make sure our Boston office is a place you actually look forward to coming to every day. At Lendbuzz, we believe in building an energetic, supportive environment that makes your day-to-day workplace experience both rewarding and fun:

Complimentary Lunches: Forget meal prepping! Enjoy delicious, catered lunches on us every Tuesday and Thursday.

Sweet Happy Hours: Take a well-deserved break with the team at our fun happy hours, featuring sweet treats, great conversations, and a fantastic opportunity to unwind and connect.

Smarter Commuting (TMA Benefit): Save money on your daily trek. We offer TMA benefits, allowing you to allocate pre-tax dollars toward your travel and transit expenses to make your commute to the city a breeze. We believe: Diversity is a competitive advantage. We celebrate our differences, and are better when we have a variety of experiences, viewpoints, and backgrounds. Compassion is a strength. We care about our customers and look to build long-term relationships with them. Simplicity is a key feature. We work hard to make our forms and processes as painless and intuitive as possible. Honesty and transparency are non negotiable. We incorporate these traits in all of our interactions. Financial opportunity belongs to everyone. We work every day to improve lives by extending this opportunity. If you believe these things too then we would love to hear from you!

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