Senior Data Scientist - (Payment Risk/Fraud) Embedded Insights

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.

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.

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.

Qualifications:

• 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 your 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.

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!

Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.

Please review our Candidate Privacy Notice here.

Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.