Senior Data Scientist

About the Project

You will join a team focused on leveraging modern AI technologies to unlock value from complex and unstructured data. Working closely with domain experts, product teams, and engineers, you will lead technical discovery initiatives, evaluate AI approaches using real-world data, and develop intelligent solutions powered by LLMs.

The role combines research, experimentation, and production implementation, offering the opportunity to build reusable AI capabilities that can be deployed across multiple business applications and data pipelines.

Your Responsibilities

• Lead technical discovery and experimentation for applied AI and machine learning use cases.
• Evaluate and compare different AI approaches using real-world datasets.
• Collaborate with domain experts to design evaluation datasets, quality metrics, and success criteria.
• Develop structured data extraction capabilities using Large Language Models.
• Design and implement Retrieval-Augmented Generation (RAG) solutions.
• Build entity resolution and entity-matching frameworks for complex datasets.
• Transform successful prototypes into reusable Python-based components and services.
• Contribute to data pipelines and AI-powered applications used across the organization.
• Partner with Product Managers, Engineers, and Business Stakeholders to scope and deliver new features.
• Own technical decisions, project delivery plans, timelines, and risk management.
• Continuously improve solution quality through evaluation, monitoring, and error analysis.

What We're Looking For

Must Have

• Proven experience delivering LLM- or ML-powered features into production environments.
• Strong programming skills in Python.
• Hands-on experience with Retrieval-Augmented Generation (RAG), structured LLM outputs, information extraction workflows, and applied AI solutions.
• Strong expertise in evaluation methodologies, experimentation, and error analysis.
• Experience working with complex, large-scale, or unstructured datasets.
• Ability to design and develop reusable software components that integrate into larger platforms and systems.
• Experience making technical decisions and taking ownership of solution delivery.
• Strong problem-solving and analytical skills.
• Ability to collaborate effectively with both technical and non-technical stakeholders.
• Fluent English, written and spoken.

Nice to Have

• Experience processing PDF documents, Microsoft Word documents, Excel files, complex tables, and multilingual content.
• Experience with Pydantic and Async Python.
• Knowledge of LLM Agents, Tool Calling, AI Observability, Tracing, and Monitoring.
• Experience with AWS, Amazon S3, Apache Airflow, Kubernetes, and MongoDB Atlas.
• Exposure to OCR technologies, Vision-Language Models (VLMs), and GPU inference and optimization.

Who Are We Looking For?

• Enjoys turning research and experimentation into production-ready solutions.
• Takes ownership of technical decisions and delivery outcomes.
• Can balance innovation with practical business value.
• Is passionate about applying AI and LLM technologies to solve real-world problems.
• Thrives in collaborative, cross-functional environments.
• Communicates technical concepts clearly to different audiences.
• Continuously seeks opportunities to improve processes, models, and product quality.
• Is excited about shaping the future of AI-driven products within a global organization.

What We Offer

• Cooperation in a B2B model.
• Benefits package for contractors: private healthcare, Multisport card, life insurance, language courses, and access to online learning platforms.
• 100% remote work.
• Opportunity to work with cutting-edge AI, Machine Learning, and Large Language Model technologies.
• Participation in strategic initiatives within a leading global pharmaceutical organization.
• Exposure to challenging data and AI problems with real business impact.
• Collaboration with experienced AI, Data, Product, and Engineering professionals.
• Long-term cooperation in an innovative and fast-growing technology environment.
• A culture that values knowledge sharing, ownership, and continuous learning.