Creating innovative financial operations solutions that help small and mid-size businesses save time, become more efficient and grow.

BILL is a leader in financial automation software for small and midsize businesses (SMBs). As a champion of SMBs, we are dedicated to automating the future of finance so businesses can thrive. Hundreds of thousands of businesses trust BILL solutions to manage financial workflows, including payables, receivables, and spend and expense management. With BILL, businesses are connected to a network of millions of members, so they can pay or get paid faster. Through our automated solutions, we help SMBs simplify and control their finances, so they can confidently manage their businesses, and succeed on their terms.

BILL is a trusted partner of leading U.S. financial institutions, accounting firms, and accounting software providers. We have operations in San Jose, CA, Draper, UT, Houston, TX and Sydney, AUS and are continuing to expand into other geographic locations. If you’re looking for a place that helps you do the best work of your career, look no further than BILL.

This position is based at our Draper, UT office. We support a hybrid work environment with on-site and remote work days.

Make your impact within a rapidly growing Fintech Company

Come join Risk Analytics at Divvy! As a data scientist, you will own key projects and grow the data science and analytics functionalities/ capabilities within Risk. You will partner closely with the Risk teams to improve how Divvy makes decisions around dynamic credit limits, payment accelerations and driving spend growth across the customer lifecycle. You will partner closely with Product, Sales, Operations and Data Engineering on data infrastructure, systems design, and how to deploy data science logic in production.

What You’ll Do

• Become the expert in our customer’s bank data, build deep insights and enable/influence decisions across the risk spectrum.
• Use that expertise to lead our efforts to expand a key area of underwriting new accounts and credit lines, including review of additional needs for software integrations and expansion
• Take ownership of several of our central decision science dashboards, enriching and expanding them to ensure optimal insights delivered to our risk and growth teams
• Build, own and develop statistical/ machine learning models by leveraging internal as well as alternative data sources. Identify customer needs and balance customer risk.
• Build out probability of default models for various risk segments/cohorts within the portfolio, estimate loss given default (LGD) and help improve portfolio risk management
• Perform detailed case reviews, identify learnings and be an integral part of improving and optimizing risk monitoring and alerting
• Closely partner with the Underwriting team to identify early customer tenure risk and create a strong handshake in moving customers effectively from onboarding to high spend growth
• Monitor losses, maintain an effective control environment and respond to gaps with speed, urgency, and discipline.
• Periodically review High Risk segments and suggest action items on accounts based on data and due diligence
• Full stack data science development: from upstream data modeling and cleaning, to research and prototyping, to deploying and monitoring models in production
• Design systems and SLAs that allow risk analytics to capture, move, store, and transform raw data into highly actionable insights with product and data engineering teams
• Contribute to Divvy’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way

We’d love to chat if you have:

• Uncanny ability and willingness to take on any kind of analytics at any level to generate key insights that lead directly to improved decisions
• Minimum 4 years of data science experience building models and dashboards (Tableau/ Power BI or similar).
• Risk management experience in the finance industry and understanding of the credit lifecycle is highly preferred
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate large amounts of data with attention to detail and accuracy
• Proficiency in SQL, Python and/or R, and Excel
• Experience to write complex queries and work with large datasets to solve complex business problems
• Ability to clearly communicate complex results to technical experts, business partners, and executives
• Good perspective on data science development cycle (problem definition, EDA + feature engineering, modeling + evaluation, deploy + monitor + iterate in production)
• Familiarity with the mathematical fundamentals of advanced statistics and optimization
• Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
• Advanced degree in Data Science, Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields
• A sense of passion, urgency and personal ownership over controlling losses and driving growth

Nice to Haves

• Experience with consumer or business credit and fraud modeling
• Experience with the modern data stack (Fivetran / Snowflake / dbt or similar)
• Familiarity with MLOps/infra required to support data science solutions
• Familiarity and experience with methods for experimental design and causal inference
• Experience at a high-growth startup

Let’s talk about benefits

• 100% paid health, dental, and vision plans (choose HMO, PPO, or HDHP)
• HSA & FSA accounts
• Life Insurance, Long & Short-term disability coverage
• Employee Assistance Program (EAP)
• 11+ Observed holidays and wellness days and flexible time off
• Employee Stock Purchase Program with employee discounts
• Wellness & Fitness initiatives
• Employee recognition and referral programs
• And much more