Senior Data Scientist - Embedded Insights

Plaid•San Francisco, CA

About The Position

The Embedded Insights team builds machine learning models to enable better internal decision making and to power the Plaid product suite. We are structured as a central team of MLEs and Data Scientists, and embed with partner teams to bring ML models to life. As the first Data Scientist on Plaid’s Embedded Insights team within the Data organization, 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. In this role, 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. A key part of your work will involve translating complex analyses into compelling, actionable narratives for technical and business stakeholders. You will design and analyze experiments, communicate findings across teams, and use data-driven insights to uncover opportunities to improve existing products and expand Plaid’s 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.
Deep familiarity with SQL and data visualization tools.
Understanding of modern machine learning techniques, such as classification, clustering, optimization.
Proven ability to tailor your solutions to business problems in a cross-functional team.
Ability to code and iterate independently in Python to conduct exploratory data analysis.

Nice To Haves

Experience building data pipelines in DBT or Airflow is a plus.

Responsibilities

Applying your expertise in quantitative analysis, data mining, and data visualization to keep the Plaid network safe and improve our product suite.
Informing and influencing product and engineering teams through your data analysis and presentations.
Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid.
Championing a data-first approach toward decision-making across the entire organization.