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
Experience with financial fraud and risk assessment, especially in a research context
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
Bachelors degree or equivalent work experience in Computer Science, Mathematics, Engineering, Economics, or a closely related field
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