Slope · 6 days ago

Data Scientist

San Francisco, CA

Full-time

Onsite

Senior Level

5+ years exp

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Responsibilities

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

Qualification

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Statistical modelingMachine learningRisk modelingPythonSQLData productsConsumer lendingPayments risk managementCredit riskFraud riskAlternative data sourcesUnderwritingData analysisStakeholder collaborationProcess creationFast-growing company experienceProject managementIterative mindsetProblem-solvingCommunicationAttention to detailWork ethicCollaborationAdaptabilitySelf-directedFintech InfrastructureHigh-Growth Startup ExperienceEntrepreneurial MindsetCustomer-CentricPassionate

Required

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