Lead Data Scientist

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Forward Financing

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2012

💸 Finance

💳 Fintech

🤝 B2B

💰 $250M Debt Financing on 2021-05

Finance • Fintech • B2B

Forward Financing is a company that provides fast and flexible financing solutions for small businesses. They specialize in offering capital to small businesses that may struggle to secure funding from traditional financial institutions. With a simple application process, businesses can receive funding decisions within hours and may have funds transferred the same day. Their revenue-based financing model allows payments to adjust with the business's revenue. Forward Financing aims to provide clear and transparent terms, ensuring customer satisfaction and trust. They have been recognized for their excellent service and are rated highly by small business owners.

📋 Description

• Design, develop and deploy advanced statistical or machine learning models for credit risk, pricing, collections, fraud, and other high-impact business use cases that drive better data-driven decisions • Lead end-to-end delivery of data science initiatives from problem framing and model design through deployment, monitoring and ongoing maintenance • Partner with cross-functional teams including Portfolio Strategy, Engineering, Product, Underwriting, Sales and Collections to integrate models into our applications, and proactively identify and solve problems in critical business areas • Define and set standards for model development, code quality, and documentation; guide technical design decisions across the team • Act as a technical mentor to team members, fostering a culture of continuous learning and rigorous analytical standards • Communicate complex technical concepts and business implications to both technical and non-technical stakeholders • Build and maintain production machine learning pipelines and monitoring systems to ensure models are reliable, scalable and continuously improving

🎯 Requirements

• 8+ years of hands-on model development and deployment experience using advanced statistical and machine learning techniques such as generalized linear models, gradient boosting and deep learning • Deep experience in building and deploying credit risk models, especially underwriting models, in the fintech, lending or financial services industry is highly preferred. • Experience with real-time models, decisioning engines, and production-grade machine learning pipelines is preferred. • Expert in Python, SQL and Git • Experience with workflow orchestration tools, such as Metaflow is preferred • Experience deploying and managing models within a cloud platform (AWS, Sagemaker) • Strong foundation in statistics and machine learning, and knowledge of experimental design • Excellent project management and communication skills • Strong critical thinking and problem-solving ability • Nice to have experience: cloud data warehouses (e.g. Snowflake, Databricks), Arize, Metaflow, Sagemaker, decision engines (e.g. Taktile), feature stores (e.g. Tecton) • Bachelor's degree in Financial/Applied Math, Operations Research, Economics, and/or Statistics. Masters/PhD is a plus.

🏖️ Benefits

• medical • dental • vision • flexible time-off policy • paid parental leave • RRSP match • wellness reimbursement • volunteering days • annual professional development budget • charitable donation match