• Own marketing analytics across DTC and Amazon, including paid acquisition, retention, LTV, and channel-level performance. • Build and maintain attribution models for DTC acquisition that account for multi-touch and organic effects—not just last-click. • Analyze Amazon performance data including traffic, conversion, ad spend efficiency, and organic/paid contribution. • Identify performance trends and surface actionable insights to growth leads on a regular cadence. • Support the Growth Marketing and Ecommerce teams on the design and analysis of A/B and multivariate tests across paid channels, email, website, and Amazon storefronts. • Set standards for test design, sample sizing, and statistical significance across the marketing team. • Support the ecommerce team on updating Marketing on website and digital storefront performance analysis. • Track and report on conversion funnel metrics, site behavior, and the impact of UX or merchandising changes. • Support the CMO and VP of Growth in the monthly revenue forecasting cycle — pulling and organizing upstream inputs, updating the growth model, and flagging anomalies or trends that warrant a closer look. • Take ownership of running and interpreting incrementality testing tool and use results to inform channel investment decisions.

Title: Data Scientist Location: San Francisco United States Location Type: Hybrid Job Description: About Us: At Parafin, were on a mission to grow small businesses. Small businesses are the backbone of our economy, but traditional banks often dont have their backs. We build tech that makes it simple for small businesses to access the financial tools they need through the platforms they already sell on. We partner with companies like DoorDash, Amazon, Worldpay, and Mindbody to offer fast and flexible funding, spend management, and savings tools to their small business users via a simple integration. Parafin takes on all the complexity of capital markets, underwriting, servicing, compliance, and customer service for our partners. Were a tight-knit team of innovators hailing from Stripe, Square, Plaid, Coinbase, Robinhood, CERN, and more all united by a passion for building tools that help small businesses succeed. Parafin is backed by prominent venture capitalists including GIC, Notable Capital, Redpoint Ventures, Ribbit Capital, and Thrive Capital. Parafin is a Series C company, and we have raised more than $194M in equity and $340M in debt facilities. Join us in creating a future where every small business has the financial tools they need. The Data Science Team Our Impact Data is core to Parafins mission to grow small businesses. Our platform partnerships and portfolio provide rich insight into SMB financial health, allowing us to create fair, automated, and broad access to financial services. As Parafin scales, the breadth and depth of our data grows with it, amplifying the impact we can have on customers and the trajectory of the business. Our Team Enthusiasm, skepticism, and respect for data are in our DNA two of our co-founders were PhD data scientists at Robinhood. Since our founding, we have grown the team to include perspectives from graduate studies in physics, mathematics, bioengineering, economics, financial engineering, and electrical engineering and professional experience at Robinhood, Uber, Lyft, Airbnb, Faire, Segment, Facebook, and Google. We value first-principles thinking, attention to detail, and craftsmanship. Our Work Our mission is to help Parafin succeed by leveraging the vast data that powers our platform. Our team partners closely with leaders across the company to drive impact. This roles scope includes: Growth: We design experiments and analyses that expand access to capital while keeping the portfolio healthy. Example projects: - Designing experiments that navigate the tradeoff between growth and risk expanding access to capital while keeping the portfolio healthy - Studying the full merchant lifecycle first offer, repayment, repeat capital to find where we can responsibly extend more - Modeling how a prospective partners portfolio would perform on our platform, so we can size new opportunities before launching Portfolio Monitoring & Servicing: We build models and tooling that forecast portfolio performance and measure the impact of our servicing efforts on merchant outcomes. Example projects: - Building and shipping ML models (XGBoost and friends) that forecast merchant repayment behavior from feature engineering through production deployment to inform how we price and size offers - Measuring whether our servicing actually works how much balance we recover after reaching out to a struggling merchant, and what interventions move the needle Infrastructure: We build the data pipelines, automated systems, and internal tools that let the rest of the company operate at scale. Example projects: - Building the data pipelines that power every analysis, dashboard, and ML model across the company - Automating processes lien filings, KYC checks, fraud screens using APIs, ML, and LLMs - Building internal tools Streamlit apps, dashboards, Slack bots that the rest of the company uses every day Beyond these focus areas, our team helps expand our impact by recruiting exceptional talent, improving our tools, and supporting each other through regular seminars and project reviews. About You Your Impact You will make an outsized impact on Parafins trajectory by leading projects from end to end. You will quickly learn new methods, apply them across diverse areas of the business, and implement them robustly. You will develop expertise in specific areas of the business, but may tackle projects across domains as our priorities evolve. Your Background and Skills Bachelors Degree (or higher) in Computer Science, Statistics, Mathematics, Data Science (or related fields). We believe the most effective data scientists bring the following skills to their work: - Statistical Reasoning - Approach data analysis with a critical, intellectually honest eye - Design concise metrics that guide decision making - Use robust causal inference methods - Develop valid and predictive machine learning models - Business Acumen - Identify and effectively prioritize business problems - Solve business problems using appropriate data science techniques - Anticipate the impact of your work on our financial performance, customers, and compliance obligations - Engineering Mindset - Write legible, reliable, and tested code - Build or source tools to boost the teams efficiency - Contribute to model and data infrastructure design - Leadership and Collaboration - Model Parafins values of efficiency, intellectual honesty, accountability, and empathy - Build trusted relationships with stakeholders - Document work, seek feedback, and share learnings proactively - Mentor other DS members on the team - Management experience, a plus! - Focused Execution - Prioritize high-impact use of your time - Scope projects rigorously - Act with urgency - AI Tool Fluency - Rapidly learn and adopt emerging AI tools and workflows to accelerate analysis - Critically evaluate AI-generated outputs for accuracy and reliability What We Offer - Salary: $200k - $235k Senior/Staff Level: $235k - $330k+ - Equity grant - Medical, dental & vision insurance - Work from home flexibility - Unlimited PTO - Commuter benefits - Free lunches - Paid parental leave - 401(k) - Employee assistance program If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please contact us.

• Support the design and implementation of IDP and AI solutions across claims • Prepare data for document processing • Transform outputs into structured datasets • Contribute to automated document extraction and data enrichment workflows • Collaborate with business stakeholders, engineers, and data scientists to translate business problems into technical solutions • Manipulate data using Python and SQL Server; develop ad hoc queries to investigate data anomalies and to summarize data for pattern detection • Manually label and validate training datasets • Use AI technologies such as natural language processing to extract business data from unstructured and semi-structured sources • Create technical documentation to archive end-to-end processes • Implement evaluation frameworks using precision, recall, F1 scores, accuracy, and operational metrics • Build solutions to monitor and continuously evaluate performance of implemented solutions • Collaborate with experienced modelers to build predictive models and analytic solutions; apply machine learning techniques such as decision trees and clustering

• Lead and coordinate the design process from project inception through construction documentation. • Review technical requirements and validate scope boundaries for design packages. • Develop and maintain the Design Management Plan. • Manage design-related Requests for Information (RFIs) and changes in coordination with the construction management team. • Conduct periodic site inspections and witness testing to verify adherence to quality standards.