Data Scientist

• Support implementation of retrieval-augmented generation (RAG) solutions using vector databases (Pinecone, pgvector).
• Collaborate with data engineers and cloud architects to integrate AI models with ERP, CRM, and workflow tools.
• Apply MLOps practices for model versioning, testing, and deployment (MLflow, Kubeflow, Vertex AI).
• Design and maintain data pipelines for structured and unstructured data.
• Monitor and optimize model performance, cost, and accuracy; implement telemetry for drift and governance.
• Interview clients to identify root causes of challenges; define and document technical and business requirements.
• Create technical documentation, presentations, and demonstrations for both technical and non-technical audiences.
• Contribute to the creation of automation accelerators and reusable code modules for the practice.
• Build and operationalize AI agents and intelligent workflows using frameworks such as LangChain, LlamaIndex, or similar tools.
• Design and deploy AI solutions across cloud platforms (Azure, AWS, GCP) using modern containerization (Docker, Kubernetes) and CI/CD workflows.
• Contribute to developing and implementing firm-approved, AI-enabled solutions for clients, in accordance with company policies on data protection, intellectual property, and professional standards.
• Stay informed about emerging AI tools and techniques and collaborate with firm leadership to identify compliant opportunities to enhance client solutions and internal processes.
• Support business development activities by contributing to proposals, proof-of-concepts, and client presentations.

Senior Consultant, Data Scientist – AI & Intelligent Automation

Learning Designer – Data Science, AI Specialist

Junior Clinical Data Manager