Data Scientist, Analytics
Discord- Full Time
- Mid-level (3 to 4 years)
Candidates should possess 5+ years of industry experience in a product-focused Data Science role, demonstrating deep familiarity with SQL and data visualization tools, and experience conducting large-scale A/B experiments. They should also have a strong understanding of the AWS stack and familiarity with modern machine learning techniques such as classification, clustering, optimization, deep neural networks, and natural language processing, along with a proven ability to tailor solutions to business problems within a cross-functional team and code independently in Python.
The Experienced Data Scientist will apply quantitative analysis, data mining, and data visualization techniques to find insights for improving Plaid’s API products, conducting large-scale A/B experiments, identifying useful signals for machine learning models, informing and influencing product and engineering teams through data analysis and presentations, and making long-term data science roadmap decisions. They will also champion a data-first approach toward decision-making across the organization and potentially help evaluate and improve ML solutions and systems.
Connects financial accounts to apps securely
Plaid simplifies financial data management for individuals and businesses by connecting various financial accounts to apps and services. Its main product is a set of APIs that allow developers to integrate financial data into their applications, enabling users to track spending, initiate payments, and access financial services all in one place. Plaid serves a wide range of clients, including app developers and financial institutions, and is used by popular apps like LendingTree and Square. Unlike many competitors, Plaid focuses on providing a comprehensive and scalable platform that supports various financial use cases, such as transactions and identity verification. The company's goal is to enhance the way users interact with their financial data, making it easier and more secure.