Machine Learning Scientist (Financial Scoring)

Lendbuzz

Boston (MA)

On-site

USD 170,000 - 200,000

Full time

4 hours ago
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Benefits offered by this job

Complimentary Lunches
Sweet Happy Hours
Smarter Commuting (TMA Benefit)

Job summary

Lendbuzz in Boston is seeking a talented Machine Learning Scientist who will develop and deploy ML models for financial data and text modalities. You will collaborate across teams to integrate models into production, validate performance, and build scalable data pipelines.

The role requires a Ph.D. in a related field and 2+ years in industry or postdoc, with strong Python, ML libraries, and communication skills. This is a full-time position in our Boston office.

Qualifications

  • Ph.D. in Computer Science, Statistics, Mathematics or a related field.
  • 2+ years of industry or postdoc experience.
  • Strong CS fundamentals including data structures and algorithms.
  • Deep understanding of machine learning models and statistics.
  • Experience with real-world messy data.

Responsibilities

  • Build machine learning and deep learning models based on financial and other modalities like text.
  • Collaborate with cross-functional teams to deploy models into production systems.
  • Analyze datasets and validate model performance.
  • Design robust, scalable pipelines and services following software engineering best practices.
  • Implement end-to-end solutions including architecture, business logic, and deployment.
  • Promote rigorous testing to ensure high-quality ML releases.
  • Stay current with ML advancements to improve solutions.

Skills

Python
Machine Learning
Statistics
Data Analysis
Communication
Algorithms

Education

Ph.D in Computer Science, Statistics, Mathematics

Tools

NumPy
Pandas
PyTorch
scikit-learn

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 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.

Responsibilities
  • 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
  • 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
A Vibrant Office Culture & Perks

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.

$170,000 - $200,000 a year

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!

Background Checks

After an offer is accepted, Lendbuzz conducts a pre‑employment background check. Any evaluation of the background check will be subject to an individualized assessment, taking into account the applicant’s or employee’s specific record and the responsibilities and requirements of the particular role.

A Note on Recruiting Outreach

We’ve been made aware of individuals falsely claiming to represent Lendbuzz using lookalike email addresses (eg @ lendbuzzcareers.com ). Please note that all legitimate emails from our team come from @ lendbuzz.com . We will never ask for sensitive information or conduct interviews via messaging apps.

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