Drive innovation and deliver impactful solutions across Consumer Tech, Enterprise Tech, and Semiconductors as a Data Science Analyst. This role merges hands-on technical expertise with client delivery management, focusing on cutting-edge projects in Generative AI, decision science, and cloud analytics.

Explore new possibilities by harnessing the power of AI and data to responsibly transform all business areas. This is an opportunity to be at the forefront of technological advancement.

Develop and fine-tune Generative AI models for NLP, Computer Vision, and multimodal applications using GenAI frameworks. Build autonomous workflows through prompt engineering and API/tool integration, utilizing orchestration frameworks like LangChain, LlamaIndex, and AutoGen. Monitor, debug, and enhance AI agents for improved context handling, error recovery, and response quality. Construct retrieval pipelines with vector databases such as Pinecone, FAISS, Weaviate, or Milvus.

Implement scalable data science workflows on Azure or AWS for marketing, supply chain, or sales analytics. Utilize cloud-native tools like SageMaker or Azure Machine Learning for model training, deployment, and monitoring. Perform advanced analytics using Python and SQL, and develop predictive models, recommendation systems, and optimization solutions with TensorFlow or PyTorch. Manage large-scale datasets, preprocessing pipelines, and feature engineering across diverse data modalities.

A strong background in Data Science and AI is essential for this role. You should possess practical experience in developing and deploying Generative AI models, including fine-tuning and prompt engineering.

Proficiency in programming languages like Python and SQL, along with experience in machine learning frameworks such as TensorFlow or PyTorch, is critical. Familiarity with cloud platforms like Azure or AWS, and their associated AI/ML services, is highly valued. Experience with vector databases and orchestration frameworks is also required.