Description
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. #LI-Remote
Plaid’s 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.
You’ll 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.
\n- Diving deep into Plaid’s 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
- 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
Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at [email protected].
Please review our Candidate Privacy Notice here.
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