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We're looking for Machine Learning Engineers 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. You’ll be a machine learning engineer 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.
Job Responsibility:
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
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
Requirements:
1-4 years years of industry experience in a machine learning or data scientist role
Deep familiarity with SQL and python
Experiencing constructing models in a regulated industry
Familiarity with the AWS stack
Understanding of modern machine learning techniques, such as classification, clustering, optimization, 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
Bachelor's degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field
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