One of our top priorities as a company is to become an industry leader in risk assessment through the use of advanced analytics. As a Senior Data Scientist, you will have an integral role in this, contributing to the research and development of production machine learning models that are part of our underwriting process (default risk, fraud, etc). You will evaluate new features from diverse data sources, use workflow orchestration tools to train models, and develop model interpretability frameworks. The ideal candidate loves diving into complex data science challenges and is passionate about contributing to the development of innovative models. Reporting to the Senior Manager of Data Science, you will work at the intersection of cutting-edge technology and business strategy, translating model outputs into actionable insights that drive business value. If you are someone who enjoys the intersection of advanced analytics, business strategy, and collaborative problem-solving, we want to hear from you!

Why you should apply:

• Meaningful work. You will make a lasting impact on the long term success of Forward Financing, and on helping us achieve our mission of helping small businesses
• You love working with data and machine learning! In this role, you will collaborate closely with our Analytics Engineering, Portfolio Strategy, Data Science and Data Engineering teams to tackle exciting data and machine learning challenges
• Flexibility is a top priority. Our teams are empowered to do what works for them. This opportunity has 100% fully remote flexibility

In this role you will:

• Design and build production machine learning models that are vital to our underwriting process (auto-approve/decline, fraud, etc), using advanced statistical and predictive modeling techniques
• Evaluate credit model performance using strategies like A/B testing and retrospective analysis of tradelines, in addition to typical techniques such as statistical and business metrics
• Identify and evaluate new features from diverse data sources to enhance model performance and robustness
• Work with cross-functional stakeholders, and demonstrate ability to understand and effectively communicate technical concepts and business objectives
• Develop and execute model building workflows using Metaflow
• Assist with monitoring production models

Requirements: 

(Even if you don’t check every box, but see yourself contributing, please apply.)

• Degree in a quantitative field such as Statistics, Mathematics, Computer Science, or related field
• 3+ years of experience in credit risk modeling in the financial services industry, preferably SMB or consumer lending
• 5-10+ years of experience developing production machine learning and/or statistical models (spanning ideation, R&D, analysis, training/testing, deployment, and monitoring)
• Experience evaluating credit model performance using strategies like A/B testing and retrospective analysis of tradelines
• Proficient in python and common ML libraries (SKLearn, XGBoost, Tensorflow/Pytorch)
• Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders

Preferred Qualifications

• Experience pairing credit models with pricing strategies
• Familiarity with SQL
• Familiarity with AWS cloud stack (Sagemaker, S3, EC2s, etc)
• Hands-on experience with DAG-based workflows, preferably using Metaflow