Senior Data Scientist

Role overview

This opportunity is for a Senior Data Scientist located in Germany and handled through a partner company that oversees the application process and follow-up steps. The assignment is centered on building an advanced AI-driven document intelligence platform that solves demanding real-world data problems. You will work at the intersection of machine learning, generative AI, and scientific data analysis to convert messy, unstructured documents into information that can be searched, understood, and acted on. The role includes substantial technical ownership, hands-on work with modern AI tools, and the chance to contribute to innovative work spanning AI and scientific research.

Key responsibilities

• Develop and refine sophisticated machine learning and deep learning models that can pull information from scanned and unstructured PDF files, including highly complex scientific content.
• Create and improve LLM-based applications using vector databases and retrieval-augmented generation methods to support semantic search and smarter document discovery.
• Manage the complete ML workflow from data preparation and feature creation through training, validation, deployment, monitoring, and ongoing tuning.
• Use scientific domain knowledge to translate advanced chemistry-related information into machine-readable formats that enable deeper analytics and AI-based insights.
• Implement scalable, secure, production-ready AI systems in AWS while maintaining strong performance, dependability, and long-term maintainability.
• Work closely with software engineers, data engineers, and subject-matter experts to integrate AI solutions into live systems and ensure they support business goals.
• Track new developments in AI, machine learning, and document intelligence to keep improving the platform and its capabilities.

Required profile

• You should bring at least 5 years of professional experience as a Data Scientist delivering machine learning solutions in production.
• A strong academic or professional foundation in Chemistry, Cheminformatics, or a closely related scientific field is needed, along with experience handling complex scientific datasets.
• Deep knowledge of Python is required, together with practical experience using AWS services such as SageMaker, Lambda, S3, EC2, or similar tools.
• Hands-on experience building applications with Large Language Models is important, including prompt design, fine-tuning, API integration, or retrieval-augmented generation.
• You should have worked with vector databases such as Pinecone, Milvus, Weaviate, Qdrant, or comparable semantic search technologies.
• Strong familiarity with ML and DL frameworks such as PyTorch, TensorFlow, Scikit-learn, or equivalent tools is expected.
• Experience in Computer Vision, OCR, Document AI, or intelligent document processing would be a strong advantage.
• Excellent analytical ability, problem-solving skills, communication, and teamwork are important for success in cross-functional settings.
• Immediate availability is preferred.
• You should be comfortable working remotely and aligning with Central European Time hours.

Benefits and additional details

• This is a fully remote engagement with collaboration scheduled around the CET time zone.
• You can start contributing right away on a high-impact, forward-looking AI initiative.
• The assignment is a short-term B2B contract of roughly 2 months, with the added value of expanding your network through innovative work.
• You will work with advanced technologies including Generative AI, LLMs, vector databases, cloud-native AI services, and intelligent document processing systems.
• The environment encourages collaboration, knowledge sharing, technical quality, continuous learning, and innovation.
• The role offers a high degree of autonomy, ownership, and flexibility, with a strong emphasis on delivering meaningful outcomes.
• You may gain access to a community of experienced AI and machine learning professionals through collaborative initiatives, mentorship, and innovation-focused projects.
• The work contributes to AI solutions designed to solve complex scientific and data-heavy challenges.

Application and privacy notes

The application is reviewed through an AI-assisted matching process to help identify strong-fit candidates quickly and fairly against the core requirements. Shortlisted profiles are shared with the hiring company, while interviews, assessments, and the final hiring decision are handled by their internal team.

By submitting an application, you acknowledge that your personal data may be processed to evaluate candidacy and shared with the hiring employer in line with applicable data protection rules, including GDPR. You may exercise data rights such as access, correction, deletion, and objection at any time.

Artificial intelligence tools may be used to support parts of the hiring workflow, such as reviewing applications, analyzing resumes, or checking responses for inconsistencies or verification signals. These tools assist recruiters but do not replace human judgment, and final decisions are made by people.