Data Scientist - Applied AI, Innovation Lab

- Strong background in software engineering and applied statistics, with a passion for development and experimentation. - Proficient programming skills in Python, including API development utilizing frameworks like FastAPI and Flask, alongside libraries such as NumPy, PyTorch, and Scikit-learn. - Practical experience in creating and deploying AI applications, particularly those using Generative AI, LLMs, and Retrieval Augmented Generation (RAG). - Knowledge of LLM orchestration frameworks (e.g., LangChain, LangGraph), vector databases, and effective prompt engineering practices. - Proven capability to handle complex data, execute statistical analysis (including hypothesis testing and regression), and implement various machine learning methods. - Familiarity with cloud environments, preferably Google Cloud Platform, and understanding of MLOps concepts for swift iterations (e.g., CI/CD, containerization). - Exceptional problem-solving abilities, comfort in dealing with uncertainty, and the capacity to manage projects from initial concept to final realization. - Strong communication and presentation skills, adept at explaining the business advantages of technical solutions. - Experience with constructing agentic workflows or multi-agent systems is beneficial. - Bachelors degree in Computer Science, Data Science, Engineering, Statistics, or a related technical discipline plus 4+ years in data science or AI engineering; a Masters degree or PhD is highly valued. A combination of education and experience may fulfill requirements.