Senior Fraud Risk Data Scientist

San Jose, California, United States

BILL

The AP, AR, and spend & expense solution that lets you create and pay bills, manage expenses, control budgets, and get the credit your business/firm needs to grow.

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Innovate with purpose

 

At BILL, we believe in empowering the businesses that drive our economy. By replacing outdated financial processes with innovative tools, we help businesses—from startups to established brands—make smarter decisions and gain control of their operations. And we don’t stop there: we’re creating the future of financial automation so businesses can spend more time on what matters.

 

Working here means you become part of a vision-driven team that’s ready to tackle challenges and build cutting-edge solutions. We value purpose, drive, and curiosity—and we thrive in a fast-paced, ever-changing environment. Whether in one of our offices in San Jose, CA, Draper, UT, or working remotely, BILLders collaborate to deliver real impact for businesses that need more time in their busy weeks.

 

At BILL, we listen, learn, and lead—fostering collaboration and a drive for continuous growth. We’re committed to building a diverse and inclusive workplace that values each person’s unique skills and experiences. Even if you don’t meet every requirement, we’d love to hear from you—you might be just what we’re looking for, whether in this role or another.

 

✨ Let’s give businesses more time for what matters.

Make your impact within a rapidly growing Fintech Company

We are looking for a detail oriented, enthusiastic and dedicated Senior Risk Data Scientist to join Bill’s Risk Data Innovation team with a focus on fraud risk. The incumbent will be working on data science projects related to key risk department initiatives. The data scientist will own key projects associated with predictive fraud detection, transaction risk modeling and fraud loss mitigation to support existing and new payment products. This individual will also design experiments to understand the impact of customer experience when leveraging machine learning in complex risk strategy changes. This position requires a person who has experience with developing machine learning models and performing advanced analytics preferably in the risk domain and also partnering with cross functional stakeholders.

We’d love to chat if you have:

  • Minimum 4 years of fraud industry experience in data science and machine learning, preferably in risk, payments or financial services domain. 
  • It is preferred this person has an advanced degree (M.S., PhD.) with 4+ years of working experience or a Bachelor’s degree with 6+ years of experience, preferably in Statistics, Physical Sciences, Computer Science, Economics, Mathematics, or a related technical field
  • Strong track record of performing data analysis and statistical modeling using Python, SQL 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
  • Experience solving problems related to risk using data science and analytics
  • Experience working with cross functional teams including product, engineering and operations and leading organization-wide initiatives spanning multiple team
  • Ability to proactively find the pain points in the current process flows and make business suggestions that are sustainable and able to have long term impact by leveraging strategic thinking, and independently provide solutions to business problems with the solid technical skills and problem solving skills

#LI

The estimated salary  range for this role is noted below for our San Jose based role.  Our ranges for each role and job level are based on a variety of factors including candidate experience, expertise, and geographic location and may vary from the amounts listed above. The role is also eligible for a competitive benefits package that includes: medical, dental, vision, life and disability insurance, 401(k) retirement plan, flexible spending & health savings account, paid holidays, paid time off, and other company benefits.

San Jose pay range$126,900—$151,800 USD

What’s in it for you? 

Redefining how businesses automate their work is a fast-paced, exciting, and fun environment. But we also have benefits and perks to ensure the magic isn’t only experienced by our customers, but by our employees as well. 

Here is a preview of some of the amazing benefits here at BILL:

  • 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

Don’t believe us? Check out our culture, benefits, and teams on our career site, LinkedIn Life, or YouTube pages.

BILL is an Equal Opportunity Employer that values diversity and inclusion. We believe our best ideas come from the unique stories, perspectives, and experiences of our team members. We welcome people of all backgrounds, abilities, and identities to bring their authentic selves and contribute to our culture.

We are committed to a transparent, inclusive hiring process that reflects our values. If you need accommodations at any stage, please contact interviewaccommodations@hq.bill.com.

Our Applicant Privacy Notice describes how BILL treats the personal information it receives from applicants.

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Category: Data Science Jobs

Tags: Classification Clustering Computer Science CX Data analysis Economics Engineering FinTech Fraud risk Machine Learning Mathematics ML models PhD Privacy Python SQL Statistical modeling Statistics

Perks/benefits: Career development Competitive pay Equity / stock options Fitness / gym Flex hours Flexible spending account Flex vacation Health care Insurance Wellness

Regions: Remote/Anywhere North America
Country: United States

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