2026 Summer Data Scientist Intern- Master's (Santa Clara, CA)

Perform exploratory data analysis on large datasets. Design and improve dashboards and reports in Tableau /Power BI to visualize metrics and trends, driving data-backed decisions. Build and implement advanced statistical and machine learning models using Python (Pandas, NumPy, SciPy, and scikit-learn), with a focus on improving supply chain processes. Write/optimize SQL to extract and join data from multiple sources. Work on GenAI and LLM projects, including fine-tuning models, creating embedding-based search systems, and developing AI-driven prototypes to enhance business operations. Develop, train, and validate machine learning models (e.g., clustering, similarity models, time-series forecasting, anomaly detection, recommendation systems) to solve complex supply chain challenges. Support model implementation by packaging code, running tests, and helping with deployment steps. In-depth understanding of supply chain management principles and practices. Strong SQL skills (joins, CTEs, window functions, performance basics) Strong Python skills for data work (Pandas, NumPy, SciPy, scikit-learn) Basic understanding of machine learning concepts and model evaluation (train/test, cross-validation, precision/recall, RMSE, bias/variance) Familiarity with big data tools such as Databricks and Apache Spark (PySpark preferred) Experience with data visualization tools (Tableau Desktop or Power BI) Exposure to GenAI / LLMs and modern ML workflows (examples: prompt design, embeddings, model selection, basic fine-tuning concepts, evaluation) Advanced working knowledge of Microsoft Excel. Currently pursuing a master's degree in computer science, data science, or another quantitative field. GPA 3.0 or above preferred Experience in supply chain topics (planning, inventory, logistics, procurement, reverse value chain) Experience building end-to-end ML projects (data prep -> model -> evaluation -> deployment) Experience with recommendation systems, similarity matching. Experience with Databricks ETL, ingestion pipelines.