Fraud Strategy Data Scientist

BILL•San Jose, CA

32d

About The Position

We are looking for a talented, enthusiastic and dedicated person to join BILL’s Fraud Risk Strategy team. The incumbent will be responsible for leading key projects associated with fraud detection, risk analysis and loss mitigation at Bill.com. This position requires a person who has experience with performing analytics, refining risk strategies, and developing predictive algorithms preferably in the risk domain.

Requirements

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve complex business problems.

Nice To Haves

Experience applying AI to accelerate data science work by designing prompts, rigorously evaluating outputs, and integrating LLMs through APIs into notebooks and automated pipelines.
Experience in experimental design, fraud typologies that involve onboarding fraud/abuse, and data/control governance, including proposal development, user acceptance definition, pre/post implementation validation, and approval workflows to ensure high quality deployments.

Responsibilities

Achieved ambitious business goals through design, creation, and execution of control strategies through direct work (complex analytical rule development, maintenance, etc) and in collaboration with Product Managers, Engineers, and Business Stakeholders.
Developed, maintained, and refined risk strategy frameworks for a domain to keep model strategy up to date with high performance with the goal of delivering on KPIs.
Built and deployed data driven and automated monitoring rules to detect and quickly respond to evolving risk trends.
Partnered with product/engineering on product/customer touchpoints for risk signal capture and treatments from strategies.
Utilized advanced analytics techniques to significantly contribute to the refinement of end to end control strategies, including experience in building complex SQL/Python scripts with minimal guidance to solve ambiguous problems.
Expertise with interpreting results and using data findings to influence decision making.
Developed flexible performance dashboards and monitoring that drill to the right level of granularity to fit the audience, business needs; covering the breadth of control strategy .
Hands on experience wrangling complex data in tools (ie. Tableau) with the focus to perform monitoring, diagnostic analytics, and share actionable stories with data.
Applied advanced knowledge of data, metrics, profiles/typologies and key indicators in the financial fraud risk domain.
Demonstrated ability to find and recommend additional enhancements within data features, data enrichment, score recalibration for existing strategies and processes.
Identify and execute new model/rules/product opportunities in order to optimize processes aligning with the business goals.
Experience in project leadership, partnering and collaborating with cross functional teams including modeling, product/engineering, operations to effectively design strategies across the lifecycle at multiple touchpoints.
Establishing business requirements, shared KPIs, guiding execution, and performing validation/maintenance.
Experience influencing cross functional team approaches.
Mentorship and support of junior team members to achieve goals.