• Collect, extract, and integrate data from various sources, including databases, REST APIs, files, and external data sources.
• Validate data quality and identify inconsistencies, errors, and missing values.
• Clean, process, and prepare structured and unstructured data for analysis and modeling.
• Design, develop, and maintain data pipelines.
• Develop and improve AI and LLM-based pipelines, including prompt engineering, agent workflows, and AI automations.
• Design and maintain data orchestration workflows and improve their reliability and monitoring.
• Build and maintain analytical dashboards and reports.
• Document data structures, SQL tables, dashboards, and data-related processes.

Programming and Data Analysis

• Python (required)
• SQL
• Pandas
• NumPy
• Scikit-learn
• Data Visualization

Machine Learning and AI

• Understanding of Machine Learning concepts
• Supervised and Unsupervised Learning
• Regression and Classification problems
• Feature Engineering and Model Evaluation
• Familiarity with common Machine Learning algorithms such as Decision Trees, XGBoost
• Familiarity with Neural Networks and Deep Learning concepts is a plus.

Strong verbal and written English skills are required.

Talented candidates without prior work experience are also encouraged to apply.