Lead Data Scientist for Credit Automation

Job description

About Fazz

Fazz is an ecosystem of financial services that comprise Fazz (Business account for Southeast Asia), StraitsX (Payments infrastructure for digital assets), and Modal Rakyat (Mutual cooperation funding for MSMEs) founded in 2016, as a result of a merger between PayFazz and Xfers, two Y Combinator alumni based in Southeast Asia.

Fazz provides business accounts that offer seamless payment, savings and credit functionalities, giving businesses equal opportunity to build, run, and grow. We cater to the warung and MSME in Indonesia under the brand Fazz Agen, and fast-growing startups and SMEs in Singapore and Indonesia under the brand Fazz Business.

Fazz’s mission is to make the future of finances accessible for every single business in Southeast Asia, where many MSMEs and the population are still underserved.

Head to our website to get to know us better: https://fazz.com/

About The Team

Fazz’s newly-formed data science team focuses on leveraging data to create solutions for an inclusive financial ecosystem in Southeast Asia to improve the lives of millions. In Fazz, data science is the key to a safe and easy-to-use all-in-one financial platform for our users. The team’s scope includes many aspects of the business, including areas related to customer onboarding, financial profiling, risk assessment, fraud detection and prevention, customer service, etc. We aim to build a platform that opens up a wide range of financial services to all our users while simultaneously protecting them as well as our business from the ensuing risks.

Roles and Responsibilities

  • The team will research on and apply data science techniques to create solutions to the challenges faced by the business. We will combine expertise from multiple disciplines of data science, including graph analytics, computer vision, anomaly detection, etc. to build the solutions
  • You will work closely with other data scientists, and other members of the data, engineering and product teams to develop data science solutions for automating and improving credit application, disbursement and collection processes. These solutions will often take the form of machine learning models that are deployed to production, but may at times be delivered in different ways. Some tasks that you will work on include:
  • Researching on the latest machine learning approaches and technologies to automate processes in credit application, disbursement and collection. This may include work in domains of credit underwriting, computer vision, natural language processing, graph analytics, etc
  • Providing thought leadership in the company on applying machine learning to credit automation
  • Work with business and product units to design and run experiments, so as to collect data for improving the team’s models
  • Work with machine learning engineers and software engineers to integrate models developed by the team to existing production systems the fraud detection solutions to existing production systems, working in collaboration with machine learning engineers and software engineers
  • Working with machine learning engineers to create mechanisms for tracking the solutions’ online performance
What we’re looking for

  • BS/MS Degree or above in Math, Statistics, Computer Science, or Engineering
  • Hands-on experience with machine learning model development in python, preferably have deployed and maintained such models in production
  • Experience and deep understanding of SQL, Python programming, Machine learning models such as random forests, gradient-boosted trees, neural networks and/or graph analytics
  • Thrive in a collaborative environment
Nice to haves (Optional)

  • Relevant experience in Payments, Retail or Consumer Financial Services
  • Familiar with Google Cloud Platform
We love reviewing all the applications we receive, but unfortunately, we may not be able to get back to everyone individually. If we’d like to move forward with your application, we’ll be in touch!

Fazz is an equal-opportunity employer. Individuals seeking employment at Fazz will be considered without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, or any other characteristic protected by applicable laws.

By submitting your application, you agree that Fazz may collect your personal data for recruiting, regional organization planning, and related purposes.

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