Data Scientist, New College Grad- Master's (Santa Clara, CA)

Assist in the design and development of AI-driven solutions, including methods, processes, and systems for analyzing structured and unstructured data from diverse sources. Support machine learning model development, including data preprocessing, feature engineering, and evaluation using Python and modern AI frameworks Collaborate with internal stakeholders to gather requirements and translate them into AI solutions that address business needs. Contribute to large language model (LLM) integration, and prompt engineering for enterprise applications. Develop and maintain data pipelines and automation scripts for model training and deployment, leveraging SQL and Python. Participate in AI experimentation and prototyping, including testing new algorithms and approaches for improving performance and scalability. Ensure timely delivery of AI-enabled tools and insights to support decision-making and operational efficiency. Programming & Scripting: Proficiency in Python for data preprocessing, feature engineering, and automation; basic SQL for data queries Machine Learning Fundamentals: Strong understanding of supervised/unsupervised learning, model evaluation, and optimization AI Frameworks: Exposure to TensorFlow, PyTorch, or Scikit-learn for building and testing models Data Analysis: Hands-on experience with Pandas, NumPy; ability to clean and manipulate structured/unstructured data Large Language Models (LLMs): Familiarity with prompt engineering and integration concepts Data Pipelines: Basic knowledge of ETL processes and workflow automation Experimentation & Prototyping: Ability to test algorithms and iterate quickly Cloud Concepts: Awareness of AWS/Azure/GCP for deployment (coursework or projects) NLP Basics: Text preprocessing, embeddings, and semantic search fundamentals Creative Problem-Solving: Innovative approach to challenges and solution design and a passion for exploring new AI techniques and tools Rapid Iteration Mindset: Comfortable with fast-paced prototyping and adapting based on feedback Collaboration & Communication: Ability to work with cross-functional teams and explain technical concepts clearly Master's Degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Physics, Cognitive Science or a related field. Exposure to large language models (LLMs), prompt engineering, or natural language processing concepts. Experience working with structured and unstructured data, including data cleaning and feature engineering. Understanding of cloud computing concepts (AWS, Azure, or GCP) through academic projects or professional experience. Ability to communicate in writing and through presentations and a desire to evangelize AI concepts. Prior internship, research, or project experience in AI, automation, or data-driven solutions is preferred.