Slope
Data Scientist
Slope, San Francisco, California, United States, 94199
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 iteratingWe 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 ownershipWe 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 worldWork with seasoned second-time foundersHelp transition the massive B2B economy online and help small business owners thriveWhat 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 segmentManage large datasets, ensuring data quality, consistency, and reliability throughout the modeling processEvaluate new private and/or public data sources; interact with vendors to assess external data productsMonitor model performance and proactively identify model deficienciesCollaborate 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 resultsCollaborate with data engineering teams to optimize data infrastructure and workflowsPrepare documentation and reports for model development and validation processes; ensure model compliance with regulatory requirements and internal risk management standardsRequirements
5+ years experience in advanced statistical modeling with strong technical skills, preferably in both model development and deploymentMaster’s or Ph.D. in Quantitative Finance, Statistics, Computer Science, Mathematics, Economics, or related fieldExperienced with machine learning concept and risk modeling techniques such as regression, decision trees and boosting; experience with building data products using LLM is strongly preferredStrong skill set with Python (including sklearn, pandas, numpy, etc.) and SQLExperience 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 preferredExcellent written and verbal communication skills; ability to clearly explain data science work and collaborate with stakeholders to executeAttention to detail, strong work ethic, and a relentless drive; enjoy a fast-paced and results-driven cultureExcel and enjoy a collaborative and in-person workplaceComfortable with handling ambiguity and creating processes from scratch. We are growing fast and still learningA 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 yearsSelf-directed and able to work with minimal supervisionIterative mindsetBonus 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 growPrevious experience building fintech infrastructurePrevious experience at a high-growth, fast-paced startup
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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 iteratingWe 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 ownershipWe 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 worldWork with seasoned second-time foundersHelp transition the massive B2B economy online and help small business owners thriveWhat 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 segmentManage large datasets, ensuring data quality, consistency, and reliability throughout the modeling processEvaluate new private and/or public data sources; interact with vendors to assess external data productsMonitor model performance and proactively identify model deficienciesCollaborate 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 resultsCollaborate with data engineering teams to optimize data infrastructure and workflowsPrepare documentation and reports for model development and validation processes; ensure model compliance with regulatory requirements and internal risk management standardsRequirements
5+ years experience in advanced statistical modeling with strong technical skills, preferably in both model development and deploymentMaster’s or Ph.D. in Quantitative Finance, Statistics, Computer Science, Mathematics, Economics, or related fieldExperienced with machine learning concept and risk modeling techniques such as regression, decision trees and boosting; experience with building data products using LLM is strongly preferredStrong skill set with Python (including sklearn, pandas, numpy, etc.) and SQLExperience 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 preferredExcellent written and verbal communication skills; ability to clearly explain data science work and collaborate with stakeholders to executeAttention to detail, strong work ethic, and a relentless drive; enjoy a fast-paced and results-driven cultureExcel and enjoy a collaborative and in-person workplaceComfortable with handling ambiguity and creating processes from scratch. We are growing fast and still learningA 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 yearsSelf-directed and able to work with minimal supervisionIterative mindsetBonus 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 growPrevious experience building fintech infrastructurePrevious experience at a high-growth, fast-paced startup
#J-18808-Ljbffr