Head of Risk Engineering

Flexbase is building the Financial Operating System designed to disrupt the largest and least digitized sector of the US economy: the $1.6 Trillion construction market. Our first product is a high limit corporate card for construction businesses, with an industry-leading 0% APR for 60-days. Similar to tech startups who couldn’t obtain credit cards until recent FinTechs disrupted the industry, SMB construction firms face similar challenges with traditional banks – except construction companies spend 10x more. Today we are growing incredibly fast with significant market demand. The total available market for Flexbase’s Financial OS for the construction industry alone is $24 billion. Flexbase is a fully remote company and this role can be performed from anywhere. The Role We are looking for a leader to build the future of data science at Flexbase! As Head of Data Science you will be responsible for hiring and managing the Data Science and Analytics Engineering teams to build data-driven systems at scale, develop the roadmap on reporting, data science products, experimental design, and be responsible for building the platforms and services necessary to support a best-in-class Risk Analytics organization. You’ll oversee projects that require extremely high development standards, deal with sensitive data, and drive significant monetary and compliance impacts. You will partner closely with the Risk Operations team to improve how Flexbase makes decisions around underwriting, fraud, experimental design, capital markets, and more. You will partner closely with Engineering on product, data infrastructure, systems design, and how to deploy data science models in production. Ultimately, you will enable Flexbase to get better every day by leveraging data to make better decisions and build better products. What You’ll DoDevelop a deep understanding of Flexbase’s risk management policies (underwriting, payments, transactions, fraud, credit limit changes) across our line of credit and other products.Hire and manage the data scientist and analytics engineering teams.Leverage a variety of first and third party data sources to improve how Flexbase thinks about underwriting businesses, detecting fraud, pricing new offerings, and ongoing risk management.Full stack data science development: from upstream data modeling and cleaning, to research and prototyping, to deploying and monitoring models in production.Develop the company roadmap by working closely with stakeholders throughout the lifecycle of prioritization: from complex business context, to well-defined objectives, to a roadmap of scoped opportunities for leveraging data science to drive business results.Design systems and SLAs that allow risk analytics to capture, move, store, and transform raw data into highly actionable insights with product and engineering teams.Research emerging underwriting and fraud trends to innovate on Flexbase’s risk systems and policies.Be a catalyst for driving best-in-class technology frameworks and tooling while staying engaged with the latest technology trends.What You NeedComfortable with machine learning, graph databases, automation, and emerging technologies to build best in class solutions.Minimum 3 years of experience in managing and building data science teams at a high-growth startup.Strong perspective on analytics engineering development cycle (data modeling, version control, documentation and unit testing, best practices for codebase development).Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents) and data orchestration platforms (Airflow, Dagster, Prefect).Strong familiarity with the mathematical fundamentals of advanced statistics, optimization, and/or economics.Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions.Ability to hold yourself and the team to high standards.Strong communication (written and verbal) and interpersonal skills. Our team has veteran founders with multiple exits, a Thiel Fellow, a McKinsey/construction exec with a Nasdaq IPO, and executives that led engineering and risk teams at Kabbage (AmEx), Citizens Bank, and UBS. The company’s backers include Hustle Fund, Soma Capital, Turner Novak, Jeff Morris Jr, Foundamental, Suffolk Construction, Equipment Share, famous angel investors, and many more Silicon Valley funds.