Chipper Cash is looking for a Sr/Staff Machine Learning Engineer on the Core Services team to join us as we continue our amazing growth trajectory.

Chipper is more than just a mobile wallet, it’s how people send money home to their grandparents for medicine, how parents send money to their children for school books, it’s how the African continent gets connected to the economy worldwide. Our products and business are growing rapidly and we need innovative thinkers and gritty explorers to help us pave the way in exciting areas like cryptocurrency, cross-border transactions, and expanding opportunities for generational wealth through access to the stock market.

Your Mission

You will have the rare opportunity to help build and further enhance a modern ML/Data stack using data powered by emerging NBU (Next Billion Users) in Africa.

The team operates in ‘Full Stack Data’ fashion: taking data in its rawest form and productionizing solutions using it across the board — from exploratory analysis...to feature engineering…to building and evaluating models over this data… to integrating into Chipper’s products …to building new tooling for our core teams… and more.

What You Will Be Doing

In addition to solving challenges relating to Product, you will also be collaborating with other units across the company, including: Compliance for deeper understanding of risk and fraud, Growth to help find bottlenecks in the on-boarding flow and track the growth of the app through various regional networks, Operations to provide a clear view into the movements of funds through the systems.

Some of the things the team works on include:

  • Architect end-to-end machine learning flows: imagine new feature ideas and design data pipelines ****to create new models, improve existing ones and deploy them. You will also be expected to keep up-to-date with the latest fraud-detection research. Example: performing Naive Bayes for fake name detection to use as a signal into our user risk scoring model.
  • Construct a Robust Data Platform to efficiently process millions of records at scale. Example: design streaming data pipeline support to help solve problems with a real-time constraint
  • Embed delightful and proactive experiences in our app by collaborating with Product. Example: craft suggestion chips using NLP techniques to help pre-populate payment notes for users in the Chipper app.
  • Build smart tooling to empower different teams to help them make better decisions. Example: Creating a GPT-3 powered ‘analyst’ Slackbot to make data accessible throughout the team.

What You Should Have

The data stack is predominantly Python + SQL, so the ideal candidate is expected to have strong experience with both of those. In addition:

  • Enjoy and have experience building scalable backend infrastructure
  • Hold yourself and others to a high bar when working with production systems
  • Take pride in taking ownership and working on projects to successful completion involving a wide variety of technologies and systems
  • Thrive in a collaborative environment involving different stakeholders and subject matter experts
  • Think about systems and services and write high quality code
  • Have experience in ML, ideally in a payments setting

Data Stack

  • PostgreSQL
  • Snowflake
  • Python

Application Stack

  • React Native
  • Node.js
  • Typescript

Chipper Cash <3’s Chipper Team Members

At Chipper Cash we prioritize people. We offer competitive salary and benefits including generous PTO that you’ll actually be encouraged to take, equity in the company, outstanding health and wellness benefits such as our new Chipper Care Policy, generous parental leave, retirement matching, a welcoming and inclusive culture that embraces the open-minded traveler with a love for humanity and all our differences, and much more.

At Chipper we know some groups of applicants will only apply if they check every box on a job opening, but we encourage you not to say no for us. If you meet 80% of the requirements, apply apply apply! We would love to speak to you.

#LI-MM1

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