Note: The job is a remote job and is open to candidates in USA. Forward Financing is a financial technology company based in Boston, Massachusetts, on a mission to unlock the capital that fuels small businesses across America. The Lead Data Scientist will drive end-to-end data science initiatives, transforming complex data into strategic decisions and automated solutions across the organization.
Responsibilities
- 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
Skills
- 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
- Expert in Python, SQL and Git
- 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
- Bachelor's degree in Financial/Applied Math, Operations Research, Economics, and/or Statistics. Masters/PhD is a plus
- 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
- Experience with workflow orchestration tools, such as Metaflow is preferred
- Nice to have experience: cloud data warehouses (e.g. Snowflake, Databricks), Arize, Metaflow, Sagemaker, decision engines (e.g. Taktile), feature stores (e.g. Tecton)
Benefits
- Medical
- Dental
- Vision
- Commuter benefits
- A flexible time-off policy
- Paid parental leave
- 401k match for US employees
- Wellness reimbursement
- Volunteering days
- Annual professional development budget
- Charitable donation match
- Employee Choice policy means that almost all of our employees get to decide where they work (from home, in the office, or a combination of both)
- People managers are empowered to find a cadence that works for their team for face-to-face time if desired
Company Overview