Staff Data Scientist

Staff Data Scientist - Fintech 

Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. We focus on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future. 

Bready* to make a change?

Toast is looking to expand the Data Science team to deliver new Data Science models to meet Toast Capital/Lending increased demands. As a Staff Data Scientist, you will design and develop end-to-end machine learning solutions for lending underwriting processes and risk management models. You will work with architects, engineers, product managers, and business stakeholders to solve business and customer problems and turn machine learning models into business impact across product lines.

An ideal candidate has experience building end-to-end data science solutions that create impact for the business. Experience in banking lending technology or a leading fintech company with substantial depth of expertise and knowledge in lending underwriting and risk management models is a plus.

About this Roll*:

• Design, develop, and deploy advanced predictive models and analytics to assess credit risk, optimise lending growth, and improve overall portfolio performance.
• Work closely with cross-functional teams, including Risk Management, Product, Engineering, and Business Strategy, to identify opportunities for data-driven improvements and align solutions with business needs.
• Monitor and analyse the performance of existing models and strategies, identifying areas for improvement and implementing data-driven refinements as needed.
• Present complex data-driven insights and recommendations to stakeholders in a clear, concise, and actionable manner, while fostering a data-driven culture within the organisation.
• Mentor and guide junior data scientists, fostering a collaborative environment and promoting the growth and development of the data science team.
• Stay current with the latest trends and developments in data science, fintech, and credit risk management, continually exploring new methods and technologies to enhance the organisation's capabilities.

Do you have the right ingredients*?

• Advanced degree in quantitative field such as Data Science, Statistics, Mathematics, Financial Engineering or related discipline 
• 8+ years of experience in data science, with a focus on credit risk modelling and lending growth strategies, preferably within the fintech lending space.
• Proficiency in machine learning, AI, and statistical modelling techniques, with a strong track record of developing and deploying successful predictive models in a business setting.
• Strong proficiency in Python and SQL and experience with data science libraries and tools such as: Spark, Scala, scikit-learn, Tensorflow, PyTorch, XGBoost etc.
• Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, task orchestration (Airflow) and AWS tooling 
• Strong understanding of credit risk management, lending practices, and regulatory requirements within the financial industry.
• Excellent communication and presentation skills, with the ability to articulate complex data-driven insights to both technical and non-technical stakeholders.
• Strong leadership skills, with experience mentoring and guiding junior data scientists

Bonus ingredients*:

• Passion for research and curiosity that calls you to go beyond “good enough” to create something innovative and exciting
• Self starter who loves to dig into different kinds of data to solve business problems and can communicate their findings to cross-functional stakeholders
• Experience in  banking lending technology or a fintech company with knowledge in lending underwriting, and risk management models.