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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