Data Scientist

Position: Data Scientist - Payments
Overview

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.

Plaid’s Data team is building data insights and models that improve how millions of users understand and grow their financial lives. We re looking for data scientists with experience applying state-of-the-art data analytics techniques to different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.

You’ll be a data scientist as a part of the Data organization, contributing to diverse, high-impact data insights and machine learning challenges. Specifically, you will focus on driving business impact, and production directions through data analysis and potentially help evaluate and improve ML solutions and systems. If you re interested in building state-of-the-art Data/ML solutions to unblock financial freedom for everyone, let s chat!

Responsibilities

• Applying your expertise in quantitative analysis, data mining, and data visualization to find insights for improving our API products

• Conducting large-scale A/B experiments

• Identifying useful signals that can be fed into machine learning models

• 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 product-focused Data Science role

• Deep familiarity with SQL and data visualization tools

• Experience conducting large-scale A/B experiments, analyzing results, and translating them into concrete recommendations

• Familiarity with the AWS stack

• Understanding of modern ML techniques such as classification, clustering, optimization, deep neural networks, and natural language processing

• 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

• Bachelor s degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field

Compensation: $174,000 - $260,000 a year. The target base salary for this position ranges from $174,000/year to $260,400/year in Zone 1. The target base salary will vary based on the job s location.

Geographic zones

Our Geographic Zones Are As Follows
Zone 1 - New York City and San Francisco Bay Area
Zone 2 - Los Angeles, Seattle, Washington D.C.
Zone 3 - Austin, Boston, Denver, Houston, Portland, Sacramento, San Diego
Zone 4 - Raleigh-Durham and all other US cities

Additional compensation in the form of equity and/or commission is 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 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.

Our mission at Plaid is to unlock financial freedom for everyone. We seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We encourage you to apply to a role even if your experience doesn t fully match the…