What you'd actually do

Formulate fraud and credit risk management strategies and controls for payments across different channels.

Build and maintain the risk strategies.

Collaborate with cross functional teams to operationalize these risk strategies.

Use data to inform insights, influence stakeholders on relative priorities, management, refining risk strategies and driving initiatives.

Define, develop, and deploy risk management methodologies and models including data science and rule-based and predictive fraud models.

Skills

Required

8 years of experience in risk management within the Fintech or financial services industries with an emphasis on fraud and credit risks
3 - 5 years in management
Strong knowledge of the fundamentals of risk strategy such as fraud detection and prevention, balancing customer experience against rising fraud threats, using data to draw insights for risk mitigation
Adept at SQL queries, reporting and presenting findings
Proficiency in Excel and other visualization tools
Strong organization and time management skills and the ability to prioritize manage multiple projects at once
Ability to collaborate effectively with Product Management, Engineering teams to convey the strategy and work through the roadmap prioritization, planning and implementation.
Extensive knowledge and experience with defining, developing, and deploying risk management methodologies and models including data science and rule-based and predictive fraud models
Expertise in driving operational efficiencies and scale through ongoing policy and model optimization.
Communicate and liaise effectively with the Compliance team and formulate the strategy for new product launches.
Experience managing cross-functional, multi-stakeholder processes, communicating and influencing stakeholders at various levels across functional boundaries
Strong analytical abilities.
Hands-on experience leveraging AI/ML tools to strengthen fraud strategy, including using LLM-based signals, anomaly detection, or generative AI to identify emerging fraud patterns and inform rule and model development
Familiarity with AI-assisted analytics platforms (e.g., Python-based ML libraries, AutoML tools, or vendor AI solutions) to accelerate fraud pattern recognition, risk scoring, and strategy iteration at scale
Demonstrated ability to evaluate and govern AI-generated outputs within a fraud risk context — including assessing model drift, managing false positive/negative tradeoffs, and knowing when to override automated fraud decisions

Nice to have

MS/MA/MBA degree preferred in Business, Economics, Finance, Analytics, Mathematics, or a related field
Familiarity with typical credit data, systems & technologies is highly valuable

Other signals

Leveraging AI/ML tools to strengthen fraud strategy

Using LLM-based signals, anomaly detection, or generative AI to identify emerging fraud patterns

Defining, developing, and deploying risk management methodologies and models including data science and rule-based and predictive fraud models

Driving operational efficiencies and scale through ongoing policy and model optimization

Evaluating and governing AI-generated outputs within a fraud risk context

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 in a remote-eligible role, BILLders collaborate to deliver real impact for businesses that need more time in their busy weeks.

BILL builds high performing teams and we seek to hire the best talent for every role. We're committed to building a workplace that fosters inclusion and diverse perspectives, valuing each person’s unique skills and experiences. 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 talented, enthusiastic and dedicated person to join Bill.com’s Risk Strategy team. This role will report to VP of Fraud Risk Strategy and will work closely with cross functional teams to formulate fraud and credit risk management strategies and controls for payments across different channels. This person will be responsible for building and maintaining the risk strategies and collaborate with cross functional teams to operationalize these risk strategies. This position requires a person who has experience with using data to inform insights, influence stakeholders on relative priorities, management, refining risk strategies and driving initiatives.

We’d love to chat if you have:

8 years of experience in risk management within the Fintech or financial services industries with an emphasis on fraud and credit risks and 3 - 5 years in management
Bachelor's degree; MS/MA/MBA degree preferred in Business, Economics, Finance, Analytics, Mathematics, or a related field
Strong knowledge of the fundamentals of risk strategy such as fraud detection and prevention, balancing customer experience against rising fraud threats, using data to draw insights for risk mitigation
Adept at SQL queries, reporting and presenting findings; Proficiency in Excel and other visualization tools
Strong organization and time management skills and the ability to prioritize manage multiple projects at once
Ability to collaborate effectively with Product Management, Engineering teams to convey the strategy and work through the roadmap prioritization, planning and implementation. Also collaborating effectively with Customer success and sales teams while dealing with escalations and effectively communicating the risk policies to the broader organization.
Extensive knowledge and experience with defining, developing, and deploying risk management methodologies and models including data science and rule-based and predictive fraud models
Expertise in driving operational efficiencies and scale through ongoing policy and model optimization.
Communicate and liaise effectively with the Compliance team and formulate the strategy for new product launches.
Experience managing cross-functional, multi-stakeholder processes, communicating and influencing stakeholders at various levels across functional boundaries
Strong analytical abilities. Familiarity with typical credit data, systems & technologies is highly valuable
Hands-on experience leveraging AI/ML tools to strengthen fraud strategy, including using LLM-based signals, anomaly detection, or generative AI to identify emerging fraud patterns and inform rule and model development
Familiarity with AI-assisted analytics platforms (e.g., Python-based ML libraries, AutoML tools, or vendor AI solutions) to accelerate fraud pattern recognition, risk scoring, and strategy iteration at scale
Demonstrated ability to evaluate and govern AI-generated outputs within a fraud risk context — including assessing model drift, managing false positive/negative tradeoffs, and knowing when to override automated fraud decisions

**Visa Sponsorship: ** Please note that this position is not eligible for visa sponsorship. Applicants must have authorization to work in the United States without requiring visa sponsorship now or in the future.

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 below. 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. The estimated salary ranges noted below roles in the specific geographic zones

Zone 1- San Francisco Bay Area CA (includes HQ), New York City, Seattle, Los Angeles County

$190,400—$238,050 USD

Zone 2- CA (Non San Francisco Bay Area and Los Angeles County), Austin TX, Massachusetts

$171,400—$214,200 USD

Zone 3 -Utah (includes Utah office), Houston TX, Florida, North Carolina

$161,800—$202,300 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. 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. To ensure a fair evaluation, our Candidate Integrity Policy prohibits the use of unapproved external assistance, including generative AI, during live interviews or assessments. Doing so will result in a review and potential disqualification.

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