Note: The job is a remote job and is open to candidates in USA. Forward Financing is a financial technology company on a mission to unlock capital for small businesses across America. The company is seeking a Principal Data Scientist to set the technical vision for data science, lead complex statistical and machine learning initiatives from concept to production, and advise senior leadership. The role focuses on credit risk, pricing, loss forecasting, modeling infrastructure, technical standards, mentorship, and cross-functional strategy.
Responsibilities
- Lead the design, development, and deployment of the company's most complex and highest-stakes statistical and machine learning models, particularly in ambiguous problem spaces with no established playbook
- Drive end-to-end delivery of flagship data science initiatives, from problem framing and model design through deployment, monitoring, and ongoing iteration
- Lead the technical strategy and architecture for Forward's modeling ecosystem, including credit risk, pricing and loss forecasting, ensuring solutions are built for long-term scalability and business impact
- Partner with senior leaders across Portfolio Strategy, Engineering, Product, Underwriting, Sales, and Collections to shape the data science roadmap, proactively identify high-value opportunities, and influence business strategy with data
- Define and enforce organization-wide standards for model development, validation, code quality, and documentation; serve as the technical authority on design decisions
- Mentor data scientists at all levels, including senior and lead team members, raising the technical bar and fostering a culture of rigorous, continuous learning
- Communicate complex technical concepts, tradeoffs, and business implications to executives and non-technical stakeholders, and represent data science in strategic planning
- Architect and evolve production machine learning pipelines and monitoring frameworks to ensure models are reliable, scalable, and continuously improving
Skills
- Deep experience in building and deploying credit risk models, especially underwriting models, in the fintech, lending or financial services industry
- 10+ 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
- Proven track record of leading high-impact data science initiatives from ambiguity to production, with demonstrated business results
- Expert in Python, SQL and Git
- Experience designing, deploying models within a cloud platform (e.g., AWS, SageMaker), including architectural decision-making
- Strong foundation in statistics and machine learning
- Demonstrated ability to influence technical direction across teams and mentor senior technical talent
- Excellent project management and communication skills, including experience presenting to executive audiences
- Strong critical thinking and problem-solving ability
- Bachelor's degree in Financial/Applied Math, Operations Research, Economics, and/or Statistics
- 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)
- Masters/PhD is a plus
Benefits
- Annual bonus: potential to earn an additional 12% annually.
- Medical, dental, vision, and commuter benefits
- 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: almost all employees can decide where they work, including from home, in the office, or a combination of both
- Flexible hours
- Virtual and in-person opportunities to get to know colleagues, celebrate team wins, and have fun together
Company Overview
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