Lead Data Scientist

Forward Financing is a financial technology company based in Boston, Massachusetts with team members throughout the United States, Dominican Republic, and Canada. The company is on a mission to unlock the capital that fuels small businesses across America. Recognized as a Best Place to Work by Built In Boston and certified as a Great Place To Work®, Forward is investing in its employees, technology, and customer experience – with long‑term success in mind every step of the way.

We are seeking a Lead Data Scientist to drive end‑to‑end data science initiatives, transforming complex data into strategic decisions and automated solutions across the organization. You will operate at the intersection of high‑level technical execution and cross‑functional business partnership, building and scaling advanced analytical solutions that deliver measurable impact across all business domains at Forward Financing.

• 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

• Mission driven company:
  Forward is a trusted source of fast, flexible funding for small businesses that have often been underserved by traditional financing options. When you join the team, you will help ensure all small businesses have access to the financial support they need to succeed.

• Flexibility is a top priority:
  Our employees are empowered to choose where they want to work (whether that’s from home, in the office, or a combination of both) with flexible hours.

• 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.

Compensation:
Annual Salary: $160,000 - $220,000 USD
Annual Bonus: You have the potential to earn an additional 12% annual bonus.

At Forward Financing, we're committed to fair and transparent compensation. We believe in providing a compensation package that recognizes your skills, experience, and the unique value you bring to our team. We take a market‑based approach to pay, regularly reviewing benchmark data to ensure our compensation remains competitive, equitable, and aligned with our…