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Senior Data Scientist
Pink ElephantData Scientist responsible for creating a Medical Decision-Support Engine using AI and medical data. Leveraging LLMs and Knowledge Graphs to enhance mental health diagnostics.
Tech Stack
Tools & technologiesNeo4j
About the role
Key responsibilities & impact- Design robust pipelines for processing Electronic Health Records (EHR) and medical literature.
- Implement rigorous multi-stage validation frameworks (Sensitivity/Specificity analysis) to ensure clinical safety and model reliability.
- Adapt Large Language Models using SFT, DPO, or PEFT (LoRA/QLoRA) for specialised medical domains and complex clinical diagnostic reasoning.
- Architect hybrid retrieval systems that combine vector databases with Knowledge Graphs to eliminate hallucinations and ensure factual grounding.
- Develop methods to make model outputs transparent.
Requirements
What you’ll need- Expert knowledge of Transformer architectures and hands-on experience fine-tuning LLMs (Llama 3, Mistral, etc.)
- Hands-on experience with Knowledge Graphs, Triple-stores, or Graph Databases (Neo4j, ArangoDB) and Graph Neural Networks (GNNs).
- Proficiency in LangChain / LlamaIndex and vector search engines (Pinecone, Milvus, or Weaviate).
- Practical experience with SHAP, LIME, or custom attention-mapping techniques for model interpretability.
- Strong background in statistical validation for high-stakes environments and handling imbalanced messy data.
Benefits
Comp & perks- Meaningful social impact: your work directly contributes to better patient outcomes, faster recovery, and a significant reduction in diagnostic errors.
- Cutting-edge stack: work at the absolute forefront of AI, combining LLMs with structured Knowledge Graphs (Graph RAG).
- Solve the "why": you won't just build a model, you'll build a system that clinicians can trust because they understand its logic.
ATS Keywords
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Hard Skills & Tools
Transformer architecturesfine-tuning LLMsLarge Language Modelsmulti-stage validation frameworksstatistical validationmodel interpretabilitycustom attention-mapping techniqueshandling imbalanced datavector databasesGraph Neural Networks