Senior Data Scientist - Payment Risk/Fraud, Embedded Insights
Plaid offers a platform that enables applications to connect with users' bank accounts, facilitating a wide range of financial services. They provide tools for payments, personal finance management, credit, and more, serving clients like Moneybox, Western Union, and Affirm. Their core product is an API that provides access to a vast network of financial institutions, allowing developers to build financial products and services.
Funding
Projects
About Plaid
Plaid is a financial technology company that enables applications to connect with users' bank accounts. It allows consumers and businesses to interact with their bank accounts, check balances, and make payments through other financial technology applications. Plaid's network connects to over 12,000 financial institutions across 20 markets, serving a global user base of over 100 million. The company provides APIs for developers to build solutions for personal financial management, credit, payments, business finances, iGaming, and property management. Key products include Auth for account verification, Link for connecting accounts, Transactions for accessing financial data, Balance for real-time checks, Assets for verifying assets, and Identity for user verification. Plaid focuses on increasing conversion, fighting fraud, and providing clean, organized financial data for smarter underwriting and other financial services.
Skills
About the Role
You will play a foundational role in building the analytics and measurement framework that supports a broad portfolio of internal and customer-facing products. You will partner closely with product, engineering, and machine learning teams to drive data-informed decision making, evaluate product and model performance, and contribute directly to the health and growth of the Plaid network. You will analyze entities across the Plaid network to better understand behavior patterns and develop metrics and monitoring systems that identify anomalies and emerging risks. You will create dashboards and reporting frameworks that provide clear visibility into machine learning model performance, while also evaluating the impact and value of these models on both customer and internal datasets. You will translate complex analyses into compelling, actionable narratives for technical and business stakeholders, design and analyze experiments, communicate findings across teams, and use data-driven insights to uncover opportunities to improve existing products and expand offerings.
Requirements
- 5+ years of industry experience in a Data Science role
- Bachelor's degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field
- Experience with Payment Risk, Fraud or Trust & Safety
- Deep familiarity with SQL and data visualization tools
- Understanding of modern machine learning techniques, such as classification, clustering, optimization
- Proven ability to tailor solutions to business problems in a cross-functional team
- Ability to code and iterate independently in Python to conduct exploratory data analysis
- Experience building data pipelines in DBT or Airflow is a plus
Responsibilities
- Apply expertise in quantitative analysis, data mining, and data visualization to keep the Plaid network safe and improve the product suite
- Inform and influence product and engineering teams through data analysis and presentations
- Make long-term data science roadmap decisions on how machine learning and data science iteration should be done at Plaid
- Champion a data-first approach toward decision-making across the entire organization
Benefits
- Medical, dental, and vision insurance
- 401(k)
- Equity