Data Scientist - JTM
Jumio Transaction Monitoring (JTM) is disrupting a $7.5 billion compliance software market by offering an innovative platform and incorporating new data sources for our bank and fintech partners to monitor their transactions for suspicious behavior helping make the financial system safer while maximizing the value and utility of critical compliance resources.
We are looking for a data scientist at JTM. In this role, you will get to work alongside various experts in customer success, product and engineering. You will analyze datasets to discover patterns, build and test models and implement them to improve our transactional monitoring system.
- Mine and analyse data from databases to create features, generate insights, drive optimization and improvement of product development.
- Develop data models and algorithms to improve the current AML rule based system.
- Develop processes and tools to monitor and analyse model performance and data accuracy in production.
- Implement end-to-end machine learning solutions in a production environment
- Keep pace with the state-of-the-art technologies in machine learning
Experience and Qualifications:
- Bachelor’s degree in Mathematics, Statistics, Computer Science, Engineering
- 3+ years of industrial experience solving analytical problems using relevant quantitative and qualitative research and analytics experience, in related business areas; or equivalent 2+years of industry experience with Master’s degree
- Experience with data scripting languages (e.g., SQL, Python, R etc.)
- Hands-on experience with machine learning frameworks such as Scikit-learn, Tensorflow and Pytorch
- Knowledge of classical machine learning techniques (clustering, decision trees, artificial neural networks)
- Knowledge of time series approaches (ARIMA, Kalman filters, sequence modeling etc)
- A strong passion for empirical research and for answering hard questions with data is required.
Great to have Experience and Qualifications:
- Graduate degree in statistics, computer science, machine learning or related quantitate field.
- Industrial experience in finance
- Familiarity with SaaS development in cloud ecosystems like AWS (e.g., Sagemaker)