Understand business problems and structure analytical approaches to solve them.
Generate proof of concepts from data that help deliver improved business results.
Prepare and pre-process datasets needed to deliver analytical solutions.
Generate distinctive risk insights that deliver improved business results.
Build and implement predictive models and other analytical solutions using both structured and unstructured data.
Collaborate with Data Engineers, ML/AI Ops, and IT teams to deploy models into production environments and monitor models performance.
Support communication of findings, implications, and performance of the models to business stakeholders.

University education (Bachelor’s degree or higher)
Ideal for fresh graduates or students finishing their degree
Working knowledge of Python and basic data science packages
Advanced knowledge of statistical and predictive modeling techniques such as machine learning models (GBM, Random Forest etc.)
Use state-of-the-art deep learning approaches (e.g. CNN, transformer, RNN/LSTM/GRU, GCN/GNN)
Strong verbal and written communication skills, especially the ability to translate technical results for business audiences
English – B2 or better
Experience with Azure and Databricks is an advantage
Experience with SQL and other programming languages is an advantage

Data Scientist

Key skills