Plaid
Data Analyst
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 builds models that help millions of people better understand and grow their financial lives. We’re looking for Machine Learning Engineers who have experience applying modern machine learning techniques—such as natural language processing, anomaly detection, optimization, and time series forecasting—across a range of product areas. We value not only strong technical expertise, but also creativity, user empathy, and a collaborative mindset.
You’ll be a data scientist as a part of the Data org, 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:
Own the process for creating hands on recommendations for incorporating cash flow insights into lending decision using best practice for account level decisioning.
Improve customer usage of Plaid insights data through custom analysis adoption specific customer need.
Act as a subject matter expert for our credit insights credit policy implementation supporting data science, engineering, Go-to-Market.
Applying your expertise in quantitative analysis, data mining, and data visualization to build models and insights.
Identifying useful signals that can be fed into machine learning models.
Informing and influencing product and engineering teams through your data analysis and presentations.
Qualification:
5–10 years of experience in data science within the financial services industry.
Deep familiarity with SQL and python.
Deep understanding of credit risk and the development of underwriting models
Hands on credit expertise building and maintaining actual credit policies for lenders
Knowledge of lending lifecycle and how to optimize each step (marketing, acquisitions, customer management, collections/recoveries)
Demonstrated ability to make data driven decisions
$190,800 – $286,800 a year
The target base salary for this position ranges from $190,800/year to $286,800/year in [Zone 1]. The target base salary will vary based on the job’s location.
Our geographic zones are as follows:
Zone 1 – San Francisco / New York City / Seattle
The base salary range listed for this full-time position excludes commission (if applicable), equity and benefits. The pay range shown on each job posting is the minimum and maximum target for new-hire salaries. Actual pay may be higher or lower depending on factors like skills, experience, and relevant education or training.
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!
To apply for this job please visit jobs.lever.co.