Bill.com is a leader in financial process automation for small businesses and mid-size companies. Making it simple to connect and do business, the Bill.com Back Office Cloud digitizes, automates and simplifies legacy payment and financial processes. With an integrated, end-to-end platform, Bill.com leverages artificial intelligence to reduce manual work, and provides a cloud workspace to help run your business anytime, anywhere. The company partners with four of the largest U.S. financial institutions, more than 70 of the top 100 U.S. accounting firms, and major accounting software providers. Bill.com manages more than $70B in annual payment volume across ACH, virtual cards, checks, and international payments. The company has offices in Palo Alto, California and Houston, Texas. For more information, visitwww.bill.com or follow @billcom.
Mission: We are looking for a talented, enthusiastic and dedicated data science leader to join Bill.com's Risk Management team. The incumbent will be responsible for managing junior data scientists as well as leading key projects associated with predictive fraud detection, transaction risk modeling and loss mitigation at Bill.com. This position requires a person who has experience with developing machine learning models and performing analytics preferably in risk domain.
Professional Experience/Background to be successful in this role:
Minimum 5 years of industry experience in data science
An advanced degree (M.S., PhD.), preferably in Statistics, Physical Sciences, Computer Science, Economics, or a related technical field
Strong track record of performing data analysis and statistical modeling using SQL, SAS or similar tools
Mastery of a wide range of Machine Learning techniques, tools, and methodologies with a demonstrated capability to apply them to a broad range of business problems and data sources
Machine Learning techniques include clustering, classification, regression, decision trees, neural nets, anomaly detection etc.
Ability to clearly communicate complex results to technical experts, business partners, and executives
Comfortable with ambiguity and yet able to steer analytics projects toward clear business goals, testable hypotheses and action-oriented outcomes
Desirable to have experience solving problems related to risk using data science and analytics
Experience with implementation of Machine Learning models
Prior team management and payment risk experience is a plus
Competencies (Attributes needed to be successful in this role):
Thought leadership/People leadership
Learning Abilities/Tech Savvy
Humble No ego
Fun Celebrate the moments
Authentic We are who we are
Passionate Love what you do
Dedicated To each other and the customer