Job Description

About Digitt:

Digitt is building the consumer finance superapp for the middle class in Latin America. We are on a mission to help our customers pay off predatory debt, improve spending and create wealth.

We have already helped thousands of people in Mexico pay off several million USD in credit card debt, save millions in interest and get back on their feet.

We have raised a few million USD from top fintech investors and are ready to continue building our fintech ecosystem. We will be launching more (quite exciting!) financial products soon.

Come join us if you’re interested in solving relevant problems, truly improving people’s lives, working with a world-class team and building a legendary company.

Your role as a Lead Data Scientist:

As a Lead Data Scientist at Digitt your job will be to develop, maintain, test and improve statistical and machine learning models that directly improve customer experience and business goals.

As our first Senior Data Scientist, you will initially be strongly focused on credit risk. You will lead the design and development of a cutting edge underwriting model, integrating alternative data and using state of the art technology.

As the company scales you will also participate in the development of models applied to growth, fraud prevention and other key operations. As a Lead Data Scientist you will also be expected to expand the team by recruiting and onboarding new candidates, as well as providing them with mentorship and support along the way.

Every model you design, develop and improve will directly impact real life customers, by enabling us to offer lower rates and better financial products for them.

What you will do:

• Develop and implement statistical and machine learning models for various areas of the company, initially with a strong focus on credit risk. As the company scales, you will also develop models to optimize customer acquisition, customer lifetime value and fraud prevention, among others.
• Test and validate models to identify factors that may affect model performance, as well as to identify improvement opportunities.
• Understand the application of those models and their relationship with business goals and business decisions. The more you understand the business, the better the models will perform.
• Present the models and their results to other key stakeholders within the organization, enabling them to improve strategic decision making. Make sure to do it in a concise, clean, organized and easy to understand way.
• Continuously test and iterate with new data sources, variables, tools and techniques that result in improvements to our models.
• Perform ongoing monitoring of the models through construction of dashboards and KPI tracking.
• Build self-service systems to enable others in the organization to leverage your work.
• Provide coaching, mentoring and support to anyone else in the company who could benefit from your knowledge, experience and skills, especially within the data science function.