Job Description

About Us

Slope is bringing the B2B economy online with a category-defining modern payments platform. Powered by our clean data infrastructure, we are building one platform to seamlessly automate B2B payment workflows.

Slope has raised $187M in equity/debt to date from Sam Altman, Union Square Ventures, Y Combinator, Tiger Global, and founders of Dropbox, Doordash, Opendoor, and Plaid.

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

Bonus points

• Entrepreneurial mindset (we encourage all employees to be future founders and this can be a great stepping stone towards that)
• Customer-centric and passionate about helping small businesses grow
• Previous experience building fintech infrastructure
• Previous experience at a high-growth, fast-paced startup

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