[Hiring] Data Scientist (pharmaceutical launch planning) @KOMMLINk

Role Description

For one of our clients in the pharma industry, we are looking for a Data Scientist (pharmaceutical launch planning).

Project name: Generate Insights from Hidden Knowledge (GIHK)

Project description:

• The services are requested as part of the GIHK project.
• The project aims to transform knowledge graphs, RAG pipelines, and enterprise data into AI-driven personas that support pharmaceutical launch planning, customer experience, and evidence-based decision-making.

Background to the assignment:

• The project requires a combination of strong software engineering skills with hands-on experience in LLM applications, agentic AI workflows, RAG, knowledge graphs, and scalable data platforms.
• This expertise is not available internally, giving the external contractor a unique position compared to the client's internal project staff.
• Provides significantly different services than the internal staff.

Tasks:

• Technical Development of Synthetic AI persona using knowledge graphs, RAG, GraphRAG, chunking strategies, and enterprise data sources.
• Technical Design and implementation of LLM-based features, agentic workflows, and AI-driven insight generation capabilities.
• Technical development and build of scalable backend services, data pipelines, and integrations for AI/ML and persona-related use cases.
• Technical translation of business and product requirements into technical concepts, user stories, and working software.
• Test, refine, and optimize AI components for quality, performance, scalability, and reliability.

Deliverables:

• Creation of comprehensive documentation with all results regarding the above-mentioned tasks with subsequent handover to the client for review and approval for further usage.

Key Technologies:

• Azure AI components, Azure OpenAI, Amazon Bedrock, OpenAI, Gemini, and Anthropic
• Agentic workflows, LangChain, LangFuse, Haystack, prompt orchestration, tracing, and evaluation
• RAG, GraphRAG, embeddings, vector search, semantic chunking, knowledge graphs
• Snowflake and enterprise data platforms for structured and semi-structured data
• Python, Rust, TypeScript, Node.js, FastAPI, Java, PostgreSQL
• Docker, Openshift, Kubernetes, and CI/CD

Qualifications

• Strong professional experience in software engineering, preferably with production-grade AI/ML or data-driven platforms.
• Hands-on experience with LLM applications, RAG pipelines, AI orchestration, and modern backend development.
• Good understanding of knowledge graphs, vector search, embeddings, chunking strategies, and unstructured data processing.
• Experience with cloud-native development, APIs, microservices, testing, CI/CD, and scalable system design.
• Ability to communicate complex technical topics clearly to both technical and non-technical stakeholders.

Requirements

• Experience with LangChain, LangFuse, agentic AI tooling, prompt tracing, evaluation, and observability.
• Experience with Azure AI components, Amazon Bedrock, Snowflake, ArangoDB, and multi-provider LLM orchestration.
• Experience with OCR, document intelligence, data extraction, or transformation of unstructured content into structured knowledge assets.
• Experience with document chunking strategies, semantic chunking, metadata enrichment, retrieval optimization, and improving context quality for RAG-based systems.

Nice to have

• Experience in pharma, healthcare, biomedical data, launch planning, or customer experience use cases.

Start

ASAP

Capacity

Full-time, 40h/week

Duration

Till end of February 2027

Location

Remote

Hourly rate

70-75 Euro/h