Staff Machine Learning Engineer for a fast growing microloan fintech

Our customer's mission is to deliver access to credit to the next billion people in emerging markets worldwide. Their unique mobile security technology gives customers the ability to afford their first smartphone on credit, using the phone itself as collateral, and then provides further access to credit to help weather life's unexpected financial surprises and climb the ladder of economic well-being.

Founded in 2015, our client has reached millions of customers in a dozen countries around the globe, including Mexico, Brazil, Colombia, India, Kenya, and South Africa, and is on a strong growth path with support from major industry partners to bring credit to the next billion emerging consumers.

The role:

You will apply your expertise in machine learning and software engineering to design, develop and scale solutions that power their data science applications. You are not interested in building one off models any more. You are an ML engineer who builds data solutions that are deployed at scale to tens of millions of users. You will join the team to build assembly lines, not to assemble cars. You will be part of a data science team on a mission to improve access to credit and technology in emerging markets with the opportunity of creating a big and real positive impact to their millions of users across the countries they operate in.

Responsibilities:

1. Collaborate with global teams to deliver massively impactful data products globally.
2. Build ML pipelines that optimize critical processes for their global lending products including anti-fraud, credit strategy and marketing optimization.
3. Improve the ML infrastructure.
4. Mentor other engineers and data scientists about best practices in ML engineering.
5. Take data products from conception to scale deployment.

Qualifications:

1. PhD or master’s in Computer Science, Statistics, Engineering or a related field.
2. 7+ years of experience as a machine learning engineer, data scientist or a closely related position with a proven track record of delivering impact.
3. Expertise in machine learning algorithms, frameworks and lifecycle: from data extraction and feature engineering to model serving and monitoring for live and batch processing.
4. Strong software design skills and high proficiency in Python and its related libraries and frameworks (e.g., Scikit-Learn, Pandas, Flask, FastAPI, etc).
5. Great interpersonal skills including strong written and verbal communication.
6. Demonstrated experience with cloud providers (AWS preferred) and related data services.