Data Scientist
Employer · UNION Biztosító
Mathematician
Software developerSystems analystFull-timeBudapest
At Union, you will join a newly established team working on a greenfield initiative to build a modern, enterprise-scale AI & Data Platform. The team is building a centralized Data Lakehouse (DLH) platform, providing a scalable and secure foundation for enterprise data management, analytics, and AI/ML workloads.
Tasks
- Collaborate with business stakeholders to identify opportunities and translate business challenges into actionable Data Science and AI use cases.
- Design, develop and evaluate machine learning models using statistical methods, supervised and unsupervised learning techniques.
- Develop predictive analytics solutions for business use cases such as customer behavior analysis, risk assessment, forecasting and process optimization.
- Explore and implement Generative AI and Large Language Model (LLM) solutions, including Retrieval-Augmented Generation (RAG) and intelligent automation.
- Perform exploratory data analysis, feature engineering and model experimentation on large and complex datasets.
- Develop scalable and reusable Data Science components using Python, SQL and Azure Databricks.
- Collaborate with Data Engineers and Cloud Platform Engineers to deploy, monitor and continuously improve machine learning models in production.
- Ensure model quality, explainability and reliability through appropriate evaluation, validation and monitoring techniques.
- Communicate analytical findings, model performance and business impact to technical and non-technical stakeholders.
- Contribute to Data Science best practices, reusable methodologies and continuous improvement of the enterprise AI & Data Platform.
Requirements
- 3 years of experience in Data Science, Applied Machine Learning, Advanced Analytics or a related field.
- Strong hands-on experience with Python and SQL, including commonly used Data Science libraries such as pandas, NumPy and scikit-learn.
- Solid understanding of statistics, probability, machine learning algorithms and predictive modeling techniques.
- Proven experience developing and evaluating supervised and unsupervised machine learning models, including classification, regression and clustering.
- Experience with feature engineering, data pre-processing, model validation and performance evaluation.
- Practical experience working with large, complex datasets and combining data from multiple sources.
- Experience with Generative AI, Large Language Models (LLMs) or Natural Language Processing (NLP) solutions.
- Familiarity with cloud-based data platforms and distributed data processing, preferably Microsoft Azure and Databricks.
- Experience with version control systems such as Git and collaborative software development practices.
- Ability to translate business requirements into analytical approaches and communicate complex technical concepts to business stakeholders.
- Strong analytical and problem-solving skills, with the ability to work independently and take end-to-end ownership of Data Science initiatives.
- Excellent professional communication skills in English.