At Plaid, we believe that the way consumers and businesses interact with their finances will drastically improve in the next few years. Our goal is to build tools and products to enable developers to create this next generation of financial services applications. Today, hundreds of companies such as Venmo, Square, and Coinbase rely on Plaid to integrate with banks and the financial system.
Plaid’s data science team is building 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 machine learning and modeling techniques -- including natural language processing, anomaly detection, optimization, and time series forecasting -- toward different product areas. We value not only technical know-how, but also creativity, user empathy, and teamwork.
Our data science culture is IC-driven -- we favor bottom-up ideation and empowerment of our incredibly talented team. We are looking for data scientists who are motivated by creating impact for our consumers and customers, growing together as a team, shipping the MVP, and leaving things better than we found them.
What excites you
Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid
Utilizing features of billions of transactions to help loan applicants access capital for personal and small-business loans, help fintech developers protect against payments fraud, and help consumers improve the safety and security of their financial accounts
Exploring new ways we can better equip users and clients with insights about spending, saving, and investing
Mentoring other data scientists and establishing a culture of modeling excellence
Championing a data-first approach toward decision-making across the entire organization
What excites us
5+ years of industry experience developing machine learning models from inception to business impact. Proven ability to tailor your solutions to business problems in a cross functional team
Deep understanding of modern machine learning techniques and their mathematical models, such as classification, clustering, optimization, deep neural network and natural language processing
Ability to code and iterate independently on top of data infrastructure tools like Python, Spark, Jupyter notebooks, standard ML libraries, etc
Strong product intuition and excitement to work fast and iteratively
Data analytics and data engineering experience is a plus
Bachelor's degree or equivalent work experience in Computer Science, Mathematics, Engineering, Economics, or a closely related field