Data Scientist / ML Developer

Company Description

The 🇬🇪 Client is the leading hospitality provider, specializing in the management and operation of upscale hotels, high-end residential projects, luxury casinos, renowned restaurants, and other leisure facilities.

Project Description

We are seeking a skilled professional to develop and deploy machine learning models that optimize operations, enhance customer experience, and generate actionable business insights across the client’s hospitality and leisure portfolio.

Requirments

• Python & Frameworks: Proficiency in Python with experience using Pandas, PySpark, Scikit-learn, XGBoost, LightGBM or PyTorch.
• ETL & Data Pipelines: Experience in designing and maintaining data pipelines. Understanding of early-stage planning, defining business requirements, and architecture design before implementation.
• Cloud & Infrastructure: Strong experience with AWS or Azure and related services such as MS Fabric. Flexibility in adapting to different cloud environments and tools.
• Visualization & BI Tools: Skills in Power BI dashboard design and optimization ensuring usability for non-technical users (naming conventions, axis labeling, visual clarity, and data validation).
• Machine Learning: Understanding of the entire ML lifecycle — from data preprocessing to model training and deployment. Experience with predictive modeling across multiple domains. Confidence in using gradient boosting models and neural networks when appropriate.
• LLM & AI Integration: Practical exposure to integrating large language models (LLMs). Understanding the fine-tuning process, data preparation in JSONL format, and collaboration with domain experts.
• Monitoring & Maintenance: Understanding of operational monitoring, alerting systems, and debugging data inconsistencies.
• BA or MS in Statistics, Mathematics, Computer Science, or similar field.
• Business acumen with proven ability to understand, analyze and problem solve business goals in detail.
• Advanced English (both written and spoken).

Duties and responsibilities

Data Engineering and Integration

• Design, develop, and maintain data pipelines.
• Ingest, transform, and model data from multiple sources into the data lakehouse/warehouse.
• Ensure data integrity, scalability, and performance optimization.

Analytics & Reporting

• Develop and optimize complex SQL queries to support analytics and reporting.
• Build and maintain datasets and semantic models for Power BI.
• Design, implement, and modify advanced Power BI visualizations and dashboards.
• Partner with stakeholders to deliver accurate and actionable insights.

AI & LLM Development

• Develop, fine-tune, and maintain large language models for enterprise use cases.
• Integrate LLM solutions with data assets and reporting environments.
• Monitor and retrain models as required to maintain performance.

Working conditions

• Mon — Fri, 9am — 6pm Ukrainian time.
• Full-time, 6 months with possible extension up to 12 months.