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Data Scientist - Risk
Company | Plaid |
Address | San Francisco, CA, United States |
Employment type | FULL_TIME |
Salary | |
Category | Software Development,Technology, Information and Internet,Financial Services |
Expires | 2023-08-28 |
Posted at | 9 months ago |
We 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.
- Diving deep into the behavior and performance of large scale machine learning models to discover new opportunities of improvements and experimentation
- Applying your expertise in quantitative analysis, data mining, and data visualization to find insights for improving our API products
- Championing a data-first approach toward decision-making across the entire organization.
- Making long-term data science roadmap decisions like how machine learning and data science iteration should be done at Plaid
- Informing and influencing product, engineering teams and customers through your data analysis and presentations
- Identifying useful signals that can be fed into machine learning models.
- Data engineering experience and data pipeline tooling (e.g. Airflow, DBT) experience is a plus
- Understanding of modern machine learning techniques, such as classification, clustering, optimization, deep neural network, and natural language processing
- Bachelor's degree or equivalent work experience in Computer Science, Statistics, Engineering, Economics, or a closely related field
- Ability to code and iterate independently in Python and utilize common data infrastructure tools like Jupyter notebooks, standard ML libraries, Spark, etc
- Familiarity with AWS stack
- Deep familiarity with SQL and data visualization tools
- Proven ability to tailor your solutions to business problems in a cross-functional team
- 2+ years of industry experience in a product focused Data Science role
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