Al Data Scientist

Programming & Software Engineering: Expertise in Python (and optionally Java, JavaScript, or C#), unit testing, and version control (Git). AI/ML Knowledge: Solid grasp of machine learning and AI concepts, model behavior, and experience with NLP or chatbots. Prompt Engineering: Experience crafting and iterating prompts, including few-shot examples and output formatting techniques. RAG and Data Handling: Familiarity with embedding models, vector databases, and unstructured data processing. API and Integration Skills: Building and consuming RESTful APIs, microservices, and handling JSON/XML data formats. Data Structures & Algorithms: Knowledge of lists, dictionaries, trees/graphs, and their application in efficient agent design. Debugging & Problem-Solving: Strong troubleshooting abilities to distinguish between model and code issues. Agile and Collaborative Mindset: Comfortable working in sprints, collaborating across teams, and communicating technical needs. Domain Adaptability: Ability to quickly learn new industry concepts for tailored agent solutions. Attention to Detail & Quality: Consideration of edge cases, proper data handling, and thorough testing. Ethical Awareness: Recognize bias, confidentiality issues, and flag questionable requests. Key Words to should be in Resume Python, SQL, REST APIs, Data Structures & Algorithms, AWS/AZURE/GCP, Docker, Kubernetes, CI/CD, Generative AI/LLM, RAG (Retrieval-Augmented Generation)