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Data Scientist

✨ Why work with us?

  • You’ll get the chance to be an early team member at a fast-growth YC startup. We truly believe it’s all about slope — not where you start but how fast we are growing and iterating

  • We are growing insanely fast and are well-funded. This is a once-in-a-lifetime opportunity to join our rocketship at an inflection point!

  • We’re a tight-knit, intense team, where you'll learn a ton and have ownership

  • We have raised capital from the some of the best VCs (Y Combinator, Union Square Ventures) and angels (Sam Altman and founders of Doordash, Dropbox, Plaid, Opendoor, Unity) in the world 

  • Work with seasoned second-time founders

  • Help transition the massive B2B economy online and help small business owners thrive 

💎 What you'll do

  • Build and deploy new models and constantly iterate on core risk models by developing new features, evaluating different modeling techniques and create differentiated strategies for each customer segment

  • Manage large datasets, ensuring data quality, consistency, and reliability throughout the modeling process

  • Evaluate new private and/or public data sources; interact with vendors to assess external data products

  • Monitor model performance and proactively identify model deficiencies

  • Collaborate closely with credit risk, customer success and GTM to align data science effort with business goals; provide timely support for questions or issues impacting customer experience or credit results

  • Collaborate with data engineering teams to optimize data infrastructure and workflows

  • Prepare documentation and reports for model development and validation processes; ensure model compliance with regulatory requirements and internal risk management standards

📈 Requirements

  • 5+ years experience in advanced statistical modeling with strong technical skills, preferably in both model development and deployment

  • Master’s or Ph.D. in Quantitative Finance, Statistics, Computer Science, Mathematics, Economics, or related field

  • Experienced with machine learning concept and risk modeling techniques such as regression, decision trees and boosting; experience with building data products using LLM is strongly preferred

  • Strong skill set with Python (including sklearn, pandas, numpy, etc.) and SQL

  • Experience with consumer / small business lending and payments risk management (credit and/or fraud); knowledge of using alternative data sources for underwriting, such as e-commerce and accounting data, is strongly preferred

  • Excellent written and verbal communication skills; ability to clearly explain data science work and collaborate with stakeholders to execute

  • Attention to detail, strong work ethic, and a relentless drive; enjoy a fast-paced and results-driven culture

  • Excel and enjoy a collaborative and in-person workplace

  • Comfortable with handling ambiguity and creating processes from scratch. We are growing fast and still learning

  • A demonstrated ability to get stuff done. In an ideal world, you’ve worked in a fast-growing company and know what we should be doing today, in one year, and in two years

  • Self-directed and able to work with minimal supervision

  • Iterative mindset

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Full-time, on-site
DATE POSTED
June 7, 2024

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