Experienced Data Scientist Payments Risk
Remote job description
We believe 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 infrastructure developers need 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 and 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 11,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Salt Lake City, Washington D.C., London and Amsterdam.
Making data driven decisions is key to Plaid's culture. To support that, we need a data science team that can apply their analytical skills to understand our users and influence decision making. This includes: building and maintaining core data sets and metrics, helping the Signal team design experiments and running in-depth follow up analyses on large scale machine learning models, and supporting, educating, and providing guidance to teams on their product decisions.
You'll be a data scientist embedded on the Signal team, working in the following areas 1) evaluate machine learning model performance (e.g., fraud detection) and communicate your findings to external customers 2) analyze product (e.g., API) usage data and help the product team translate insights into potential product features 3) conduct proof-of-concept data analysis and work with machine learning engineering team to develop new data features 4) serve as a subject matter expert on the machine learning aspect of the product and engage external customers to drive sales growth and product engagement
What excites you...
- Applying your expertise in quantitative analysis, data mining, and data visualization to find insights for customer engagement with our API products
- Running impactful inferential analyses and data investigations to identify recurring patterns, root causes, and propose actionable product solutions
- Diving deep into the behavior and performance of large scale machine learning models, to identify new opportunities of improvements and experimentation
- Informing and influencing product and engineering teams through your data analysis and presentations
- Championing a data-first approach toward decision-making across the entire organization
- Mentoring and growing other data scientists into senior roles and establishing a culture of statistical excellence
- What excites us...
- 5+ years of industry experience in a Product Data Science role
- Deep understanding of various statistical and machine learning techniques
- Strong familiarity with SQL, data visualization tools, and working knowledge of Python
- Data engineering experience and data pipeline tooling (e.g. Airflow, Redshift) experience is a plus
- Bachelor's degree or equivalent work experience in Computer Science, Mathematics, Statistics, Operations Research, Economics, or a closely related field
- 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 firstname.lastname@example.org.
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Company name: Plaid
Remote job title: Experienced Data Scientist Payments Risk