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Title: Experienced Data Scientist – Credit
Location: United States
Type: Full-time
Workplace: remote
Category: Engineering
JobDescription:
We believe that the way people interact with their finances will drastically improve in the next few years. Were 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. Plaids 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. #LI-Remote Plaids Machine Learning team is building models, services and platforms that improve how millions of users understand and grow their financial lives. We are looking for data scientists who can help our clients make the best use of our products and additionally uncover insights to power our machine learning roadmap. Youll be a data scientist on the Machine Learning Credit team. You will be providing detailed data exploration and analysis, conduction A/B experiments, creating dashboard and alerts, developing metrics and build new features for evaluation of ML model performance.Responsibilities
- Diving deep into Plaids unique data to identify emerging credit risk vectors
- Running large scale A/B experiments to test new product features and evaluate different ML models and credit risk rules
- Crafting metrics, alerts, and dashboards to monitor ML production model and credit risk engine performance
- Building data pipelines using tools like DBT to automate ETL processes
- Developing new features to improve ML models at Credit
Qualifications
- 5+ years of industry experience in a product focused Data Science role
- Deep familiarity with SQL and data visualization tools
- Experiencing conducting large scale A/B experiments, analyzing results and translating them into concrete recommendations
- Familiarity with AWS stack
- Understanding of modern machine learning techniques, such as classification, clustering, optimization, deep neural network, 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