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Data Scientist Machine Learning - Credit

Data Scientist Machine Learning - Credit

PlaidSan Francisco, CA, United States
18 days ago
Job type
  • Full-time
Job description

Data Scientist Machine Learning - Credit

Join to apply for the Data Scientist Machine Learning - Credit role at Plaid

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.

Plaid’s Data team is building models that improve how millions of users understand and grow their financial lives. We're looking for data scientists 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. We value not only technical know-how, but also creativity, user empathy, and teamwork.

Responsibilities

  • 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.

Qualifications

  • 1-4 years industry experience in a financial services Data Science role.
  • Deep familiarity with SQL and Python.
  • Experience 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.
  • Salary : $162,000 - $222,000 a year (Zone 1). Additional compensation may include equity and / or commission. Benefits include medical, dental, vision, 401(k).

    Our mission at Plaid is to unlock financial freedom for everyone. We are committed to building a diverse team that cares deeply about making the financial ecosystem more equitable. We encourage applicants who bring unique perspectives to apply.

    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 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 accommodations@plaid.com.

    Please review our Candidate Privacy Notice here.

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    Data Scientist • San Francisco, CA, United States

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