Director, Data Science

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 a rapidly growing fintech company on a mission to revolutionize small business lending, and we believe the strategic use of data and models is the key to achieving this goal. Our proprietary platform leverages data and technology to provide fast and flexible financing to underserved businesses across the country. We are seeking a Director of Data Science to lead our data science team, and our initiative to deploy models that will drive better decisions and automation across the organization. This is an exciting opportunity to join our leadership team, build out a data science team, and have a meaningful impact by shaping our modeling strategy and embedding data and models into our most critical business decisions.

Responsibilities

• Lead the data science team to develop, validate, and deploy advanced machine learning models related to credit risk, fraud, pricing, collections and operations, that drive better decisions, automation, and profitability

• Oversee the full model development lifecycle (from ideation and data exploration to production deployment and performance monitoring)

• Collaborate 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 that impact critical areas of the business

• Build and mentor a high-performing team of data scientists and machine learning engineers, strategically looking at long-term staffing needs (12+ months) and raising the bar on talent and performance across the function

• Accountable for the planning, budgeting, and execution for the Data Science function by forecasting needs over multiple quarters

• Communicate complex technical concepts and model results to both technical and non-technical stakeholders, including senior leadership

• Stay current on industry trends and research in machine learning, credit risk and relevant data sources

Qualifications

• 10+ years of experience in data science, with an extensive background in credit risk modeling and relevant data sources (credit bureau, bank, public records, etc.)

• 4+ years of leadership experience managing and mentoring a team of data scientists and/or machine learning engineers

• Proficient in building machine learning models using foundational statistical methods, like generalized linear models, and advanced techniques such as gradient boosting and deep learning

• Proficient in Python

• Proficient in SQL

• Proficient in Git and code collaboration

• Experience with workflow orchestration tools, such as Metaflow

• Experience deploying and managing models within a cloud platform (AWS, Sagemaker)

• Strong statistical foundation and knowledge of experimental design

• Excellent project management and communication skills

• Nice to have experience: Snowflake, Databricks, Metaflow, Arize, 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 Targeted Salary: $240,000– $300,000 USD

Annual Target Bonus: 20%

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 performance-driven culture.

Final offers are determined by a variety of factors, including the candidate's qualifications, relevant experience, specific skills, and internal equity. This approach ensures that our compensation is competitive and equitable. Your recruiter will provide specific details on the expected base and variable earnings as it pertai