Senior Data Scientist - Embedded Insights

Plaid•San Francisco, CA

13d•$190,800 - $262,800

About The Position

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.

Requirements

6+ years of industry experience in Data Science or a related analytics role.
Deep familiarity with SQL and data visualization tools.
Understanding of modern machine learning techniques, such as classification, clustering, and optimization.
Experience evaluating model performance, identifying opportunities for improvement, and connecting technical results to business outcomes.
Proven ability to tailor analytical solutions to business problems while working with cross-functional partners.
Ability to code and iterate independently in Python, particularly for exploratory data analysis.
Strong written and verbal communication skills, including the ability to explain analytical methods, tradeoffs, and recommendations to technical and non-technical audiences.
Bachelor’s degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field.

Nice To Haves

Experience building or partnering on data pipelines using dbt or Airflow is a plus.

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.
Designing experiments, defining success metrics and guardrails, analyzing results, and communicating recommendations to stakeholders.
Analyzing Plaid product and customer data to identify opportunities for product improvement and expansion.
Partnering with cross-functional teams to build reliable data models and analytics workflows.