Lead Data Scientist

In this role you will:

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

Why you should apply:
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.

Role 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/Apfplied 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.

Our Core Values:
Drive the Mission: We believe in financial opportunity for underserved small businesses. We say “yes” when others say “no.”

Keep It Real: We value direct communication, candid feedback, and authenticity. We are an open book.

Act With Kindness: We create an environment where caring is cool and helping is the norm. We do the right thing.

Shoot for Extraordinary: We are inspired by innovative thinking and continuous improvement. We never settle for yesterday’s best.

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