Data Scientist

About Fintech Farm

We are a UK fintech creating successful neobanks in emerging markets in partnerships with local traditional banks.

Our success builds upon a best-in-class product, customer experience, emotional engagement, viral marketing, and deep credit decisioning expertise.

One of our founders had previously co-founded a highly successful Eastern European neobank with a multi-million customer base.

We launched our first market with Leobank in Azerbaijan in 2021, where we have already established market-leading positions. Our next market was Vietnam, where we launched Liobank in early 2023 and also gained solid traction.

We have a few more new markets in the pipeline for the next 12 months, and we are starting to build the team there.

Why Fintech Farm is a great place to be

Our ambition. We are looking to become a leading consumer digital bank brand in each market we operate making it easy for consumers to interact with their money. You could be a part of this exciting journey.

Our culture.

Customers. We always go above and beyond to provide an amazing customer experience. We serve our customers the way we would want our mom to be served. And who said that banking has to be boring? We make our apps not just easy but fun to use.

People. We are all business partners in our company. Each of us thinks big, acts as if we own the place, and never takes “No” as an answer. We work with strong individuals whom we empower and trust rather than micromanage. Common sense rather than formal policies prevails in all that we do. We always stay curious and open-minded. We embrace the We over Me culture.

Responsibilities:

• Develop and implement risk-scoring models to assess client creditworthiness, including both application and behavioral models.
• Perform feature engineering processes to enhance the quality and efficiency of predictive models.
• Analyze data to identify new opportunities and trends that can be utilized to improve scoring models.
• Collaborate with development teams and business analysts to integrate models into business processes.
• Monitor and analyze the performance of models in production, and propose and implement improvements.

Requirements:

• 2 to 4 years of experience in Data Science, with proven experience in building scoring models.
• Deep knowledge and practical experience in machine learning and statistical analysis.
• Experience with the Python programming language and libraries for data processing and machine learning (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch).
• Skills in feature engineering and model selection for solving specific tasks.
• Ability to analyze large volumes of data and turn analytical insights into concrete actions.
• Experience with SQL and databases.
• Ability to work independently and as part of a team, as well as interact with non-technical colleagues.

What we are offering

• Competitive salary negotiable depending on the candidate’s level
• Share options
• We are still a start-up and more benefits are on the way