Senior Data Scientist @ Antal

• Approximately 3+ years of experience as a Data Scientist
• Experience with at least one model deployed to a production environment
• Very good knowledge of SQL
• Hands-on experience with classification models on tabular data, e.g., logistic regression, gradient boosting
• Very good knowledge of feature engineering
• Ability to select metrics and validation methods
• Experience in designing and evaluating experiments
• Knowledge of model explainability methods, e.g., SHAP
• Fluent programming skills allowing for independent conduct of experiments and model development
• Ability to critically analyze data and assess its impact on model quality
• Knowledge of modern approaches to Machine Learning and AI, including conscious use of LLMs
• Ability to clearly present results to non-technical stakeholders

Nice to have:

• Experience in fraud detection, AML, or credit risk
• Knowledge of the financial or insurance sector
• Experience with graph data / graph analytics, e.g., Neo4j
• NLP, especially for the Polish language
• Model monitoring post-deployment
• Knowledge of Java
• Experience collaborating with developers within a single repository, including code review and tests

Tech stack:

The project utilizes, among others:

Java | Spring | Hibernate | Kafka | Azure | Neo4j | Angular

Senior Data Scientist

Warsaw | hybrid: 1 day in the office / 4 days remote
120–150 PLN/h net + VAT, B2B
Long-term project

About the project:

You will join a team developing a modern fraud detection system, utilizing Machine Learning, AI, and advanced data analysis.

As a Senior Data Scientist, you will be responsible for the full lifecycle of models, from data analysis and feature engineering, through experimentation and validation, to deployment and performance evaluation of the model in the production environment.

This is a role for someone who combines a solid Data Science / Machine Learning toolkit with the ability to understand business problems and translate them into appropriate analytical solutions.

We offer:

• Long-term cooperation
• Work on solutions utilizing Machine Learning, AI, and advanced analytics
• Opportunity to work on the full model lifecycle, including the production deployment stage
• Collaboration with an experienced technical and business team
• Private medical care LuxMed
• MultiSport card

,[Building, developing, and maintaining models that detect and assess fraud risk, Conducting the full model workflow: data preparation, feature engineering, modelling, validation, explainability, and deployment, Working with various data types, including tabular, text, and graph data, Selecting appropriate ML methods, metrics, and validation approaches, Designing and evaluating experiments, Analyzing new methods and data sources, Explaining model behavior using methods such as SHAP, Documenting results and presenting them to technical and business stakeholders, Collaborating with developers, analysts, and business experts, Evaluating when the use of LLMs has business and technical justification, and when classic ML would be a better solution] Requirements: SQL, Machine Learning, AI, LLM, Angular, Azure, Kafka, Hibernate, Java, Spring, Neo4j, NLP