Business Analyst - Trust, Safety, and Fraud Analytics

Your Responsibilities

Strategic Planning & Measurement: Partner with Fraud leadership to define the strategy for measuring program health, operational performance, and magnitude of Fraud’s impact on our business. This includes establishing comprehensive metrics, developing crisp reporting, and setting up monitoring rhythms.

Performance Analysis: Conduct in-depth analysis of key Fraud metrics to identify emerging trends and opportunities which will inform deeper research and analytical efforts.

Develop and refine detection models: Develop and improve tooling and models to more effectively identify emerging fraud attacks, empowering the Fraud team to take quicker, more effective action to mitigate fraud across Rover's platform.

Executive Communication: Develop and present crisp narratives resulting from analytics findings and investigations to senior Operations leaders, focusing on both identified problems and proposed solutions.

Thought Partnership: Serve as a strategic partner and advisor to business leaders, making data-driven recommendations on investments and optimization strategies within Trust and Safety and Fraud.

Your Qualifications

At least 4 years experience working cross-functionally with complex datasets to support organizational decision making.

Excellent verbal and written communication skills. Specifically, you know how to narrate analysis and results to business partners in a useful, concise, and meaningful way.

You have a passion for developing and embracing new ways of working using AI tools, with a strong desire to automate mundane tasks and develop more efficient analytical / technical workflows.

You are extremely comfortable with receiving stakeholder questions and independently translating them into clear, actionable analytical problems to solve, all with relative autonomy.

You have hands-on experience building out data abstractions using tools such as DBT or Airflow as well as a variety of data visualization tools (e.g., Mode, Looker, Periscope, Tableau, etc.)

Strong proficiency with SQL. You would feel confident reviewing code produced by other analysts and data scientists

Nice to Have

Masters degree in a quantitative field OR on the job experience with applied statistics.

Ability to code in Python/R is a plus

Prior experience performing advanced fraud analytics within the technology sector.

Experience with the development and optimization of machine learning models

Hands on experience using AI tools (Claude Code, Codex, etc) daily to simplify analytical work

Hands-on experience working with customer service tool data (e.g., Zendesk)

Hands-on experience running A/B tests and experiment design