Data Scientist

🚀 Senior Data Scientist – LLM / GenAI (100% Remote) We’re working with a Client that’s building real, production-grade LLM systems to power growth analytics and strategic decision-making. This team isn’t experimenting in notebooks. They’re deploying retrieval-grounded AI at scale, working with large, messy document datasets, and setting standards for how GenAI is used in a regulated environment. If you enjoy owning systems end to end and care about accuracy, grounding, and impact, this role is worth a look. What You’ll Be Working On • Designing and deploying retrieval-grounded LLM systems, from standard to advanced RAG patterns • Building pipelines to ingest, transform, and normalize large internal and public datasets • Processing complex documents including PDFs, HTML, and scanned content, using OCR, layout-aware parsing, and table extraction • Developing LLM-driven information extraction workflows with structured outputs, validation, and accuracy evaluation • Owning the full retrieval stack: chunking strategies, embeddings, indexing, hybrid retrieval, reranking, and relevance tuning • Integrating web-based data sources with safeguards like retries, rate limiting, and change detection • Establishing evaluation and monitoring practices to ensure grounded, reliable outputs in production • Partnering closely with analytics and business stakeholders to turn ambiguous questions into measurable outcomes What You Bring • 4+ years of experience in data science or applied ML, with deep focus on NLP and GenAI • Strong hands-on experience building LLM-based retrieval or information extraction systems used in real-world production settings • Proficiency in Python and SQL, with a strong engineering mindset • Solid experience with Databricks, Spark, and lakehouse architectures • Deep understanding of vector search concepts including embeddings, hybrid retrieval, and reranking • Experience working with semi-structured and unstructured data such as PDFs, tables, forms, and web content • A strong grasp of grounding, attribution, and evaluation techniques that reduce hallucinations • Ability to clearly communicate tradeoffs and recommendations to both technical and non-technical partners Tools & Tech You’ll Use • LLM and orchestration frameworks: OpenAI, Google GenAI, LangChain, LangGraph • Retrieval and vector tooling: FAISS, Elasticsearch/OpenSearch, Pinecone, Weaviate, Milvus, Chroma • Supporting libraries: Pydantic, Tenacity, BeautifulSoup, Pandas, NumPy Nice to Have • Experience with agentic workflows and tool-calling patterns • Background working in regulated environments with governance, auditability, and access controls Why This Role You’ll be joining a team that treats GenAI as a core capability, not a side project. The work is technical, impactful, and highly visible, with real ownership from ingestion to production. If you’re excited about building reliable LLM systems that actually get used, this is a strong next step.