Senior Product Data Scientist

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 San Jose, CA. We support a  hybrid work environment with on-site and remote work days.

Make your impact within a rapidly growing Fintech Company

Our Product Analytics and Data Science team is growing! We’re looking for a proven data scientist to join us and contribute to shaping the future direction of the company. Part of this role is tactical; you’ll be responsible for finding data, analyzing it and creating models for the Product/Sales/Ops teams. The other part is strategic: you’ll be a thought partner in measuring our product performance and identifying opportunities to improve it. 

What You’ll Do

• Collaborate with product teams to identify key performance indicators (KPIs) and build metrics that measure the impact of new products on customers.
• Develop interactive dashboards that enable teams to analyze data and gain insights into customer behavior, product performance, and business trends.
• Promote a culture of experimentation and A/B testing to drive innovation and optimize product performance.
• Enhance understanding of the customer lifecycle by conducting analyses and providing insights to help finance and research teams identify growth opportunities.
• Collaborate with cross-functional teams, such as marketing, sales, and engineering, to ensure that data is being used effectively to drive business outcomes.
• Work closely with Data Warehousing and BI engineering teams on enhancing our data to help related teams move more quickly.
• Develop, validate and monitor machine learning models to predict customer behavior, product performance, and business trends.

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)
• 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 
• 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)
• 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

• FinTech experience
• Familiarity with MLOps/Model Deployment required to support data science solutions
• Familiarity and experience with methods for experimental design and causal inference

Let’s talk about benefits

• 100% paid employee 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