Senior Data Analytics Engineer – Risk, Fraud and Disputes - Remote

Overview

We are looking for a highly analytical and technically proficient Senior Data Analytics Engineer to join our Risk, Fraud, and Disputes Engineering team. In this cross-functional and strategic role, you’ll own the design and development of scalable, reliable data assets that drive real-time fraud detection, dispute operations, and regulatory reporting. You'll be instrumental in bridging data engineering with analytical needs, enabling high-quality decisions through structured, labeled data and actionable insights using ML models.

In Short

• Partner with risk/fraud/dispute engineers, data scientists, and product managers to understand business needs and translate them into data-driven solutions.
• Lead the creation of labeled datasets to support supervised machine learning and rules-based fraud detection and chargeback prediction.
• Partner with ML engineers and backend teams to productionize data.
• Analyze large transactional, fraud, and chargeback data to uncover trends, detect anomalies, and support deep-dive investigations.
• Create and maintain real-time dashboards and reporting for key KPIs across Fraud, Risk, and Disputes for leadership, operations, and product teams.
• Recommend data improvements to enhance fraud and chargeback detection capabilities and reduce false positives/negatives.
• Act as a domain expert in fraud and dispute data, supporting internal investigations and external customer data queries.
• Partner with Finance or Operations to answer questions about dispute costs, win/loss rates, and more.
• Collaborate with Engineering to develop and maintain Airflow pipelines and ETL workflows to support scalable data pipelines.

Requirements

• 5+ years of experience in data analytics, data science, or data engineering, preferably in fraud, risk, dispute, payments, or financial services.
• Advanced SQL skills with a strong understanding of analytical functions, performance tuning, and ETL best practices.
• Deep understanding of risk, fraud signals, disputes domain or related data patterns.
• Strong data intuition: able to translate vague problem statements into structured data analysis or model features.
• Experience with data visualization tools (Looker, Tableau etc).
• Ability to translate business needs into technical solutions and data structures.
• Comfort working with ambiguous data problems in a fast-paced, high-stakes environment.
• Strong communication and collaboration skills—ability to work cross-functionally with Product, Engineering, and Ops.
• Familiarity with Airflow, dbt, or equivalent ETL/ELT tooling.

Benefits

• Multiple health insurance options
• Flexible vacation time
• Retirement savings program with company contribution
• Equity in a publicly-traded company
• Monthly stipend to support our remote work model
• Annual “development dollars” to support our people growth and development