Senior Data Scientist - Embedded Insights

About the Team

At Embedded Insights, we find the best machine learning opportunities for external products and internal systems, and collaborate with cross-functional partners to bring them to life. We are a central team of Machine Learning Engineers and Data Scientists. We embed with partner teams to build and apply machine learning models that improve internal decision-making and power the Plaid product suite.

About the Role

You will be the first Data Scientist on the Embedded Insights team, part of Plaid’s Data organization. You will establish the analytics and metrics backbone for a team supporting a diverse set of internal and external products. You will help drive better decision-making, support machine learning model development, and contribute directly to the health of the Plaid network and the quality of Plaid’s products.

What excites you about this role:

• Applying quantitative analysis, data mining, and data visualization to help keep the Plaid network healthy and improve our product suite.
• Informing and influencing product and engineering teams through rigorous analysis, thoughtful presentations, and clear recommendations.
• Turning ambiguous business questions into structured analytical approaches and measurable outcomes.
• Helping shape long-term data science and machine learning roadmaps, including how teams iterate, evaluate, and make decisions.
• Establishing analytics practices and frameworks from the ground up as the team’s first Data Scientist.
• Championing a data-first approach to decision-making across Plaid.

Responsibilities

• Analyzing entities across the Plaid network to understand behavior and identify opportunities, anomalies, and risks.
• Creating foundational metrics, dashboards, and monitoring systems that provide a clear view of network health and machine learning model performance.
• Evaluating the value and performance of machine learning models using customer and internal data.
• Identifying opportunities to improve existing models and translating findings into clear, actionable narratives for product and engineering leaders.