Product Manager - Machine Learning (Signal)

San Francisco

Applications have closed

Plaid Inc.

Plaid helps companies build fintech solutions by making it easy, safe and reliable for people to connect their financial data to apps and services.

View company page

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 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.
Develop industry leading and customer-facing transaction risk monitoring platform and  decision engine. They will develop model(s) with incredible recall and precision around transaction returns. Specifically, they will focus product development on improvements to model performance, feature engineering, stability, and coverage. They will experiment with new modeling approaches and strategies, as well as integrating third party data. 

What excites you:

  • Building an industry defining transaction risk model, using Plaid’s rich data network
  • Developing new model approaches and frameworks
  • Evaluating impacts of new data sources on model performance
  • Collaborating hand-in-hand with engineering, design, go-to-market, and operations partners
  • Huge area of strategic growth / focus: Money Movement has the potential to develop into the next $1B for Plaid, you have the opportunity to help build the next big business

What excites us:

  • Data Platforms Experience: Experience building data platforms and tools used by product teams. 
  • Highly Technical Product Experience: Minimum 3 years of experience leading highly technical product development (machine learning, computer vision or robotics) 
  • Ability to generate crucial product insights through quantitative and qualitative analysis
  • In-depth knowledge of modern software development and machine learning engineering practices
  • Fintech product development: Preferably have had experience building products which require fraud/credit/financial risk assessment such as underwriting, pricing, fraud detection, trust, and safety
  • Deep payments experience: Payments is a unique space, an understanding of payments roles, economics, and players can be very helpful. 
  • Entrepreneurial mindset or startup experience
  • A Bachelor's degree in a 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 accommodations@plaid.com.

Tags: Computer Vision Economics Engineering Feature engineering FinTech Machine Learning Robotics

Perks/benefits: Career development Health care Startup environment

Region: North America
Country: United States
Job stats:  3  1  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.