Data Scientist II, New College Grad- Master's (Santa Clara, CA)
About The Position
Join our dynamic Supply Chain Analytics team as a Data Scientist! Our mission is to revolutionize efficiency by harnessing the power of machine learning, statistical and simulation modeling, generative AI, and actionable insights. We are dedicated to transforming process efficiency through deep analysis, cutting-edge visualization, and enhanced UI/UX. Our goal is to elevate decision support systems and measurement capabilities, driving substantial improvements in key business metrics. Be a part of our journey to make a significant impact! AI has changed how fast a data scientist can move. It has not changed what makes one good. We look for people who use AI tools aggressively to move faster, and who can still explain every line they ship, defend the assumptions behind a model, and recognize an answer that is fluent but wrong. Strong fundamentals first, AI as a multiplier.
Requirements
- Master's degree in Data Science, Operations Research, Engineering, Computer Science, Statistics, Supply Chain Analytics, or another quantitative field.
- GPA of 3.0 or above preferred.
- Demonstrated skills in data science and business analytics.
- Understanding of supply chain management concepts (planning, inventory, logistics, procurement, repair operations, reverse value chain).
- Strong database fundamentals (RDBMS concepts, relational and dimensional data modeling, normalization, keys and constraints, indexing, query execution plans).
- Strong SQL skills (joins, aggregations, subqueries, CTEs, window functions, query optimization).
- Big data fundamentals (distributed processing, partitioning, columnar and table formats, Spark and lakehouse architecture).
- Data engineering fundamentals (ETL/ELT, ingestion from multiple source systems, pipeline design and orchestration, data quality and validation).
- Strong Python skills for data analysis and machine learning (Pandas, NumPy, SciPy, scikit-learn).
- Machine learning fundamentals (supervised and unsupervised methods, feature engineering, cross-validation, evaluation metrics, overfitting and regularization).
- Statistical fundamentals (distributions, sampling, hypothesis testing, experimental design, correlation versus causation).
- Hands-on experience with Databricks or a comparable cloud data platform (Snowflake, BigQuery).
- Data visualization with Tableau and/or Power BI.
- Applied GenAI and LLM experience (prompting, retrieval augmented generation, LLM APIs, agentic workflows, output evaluation).
- Knowledge of Six Sigma, Lean, or DMAIC process improvement methodologies.
Nice To Haves
- Knowledge of supply chain circular economy and reverse value chain processes.
- Machine learning or AI solutions taken end to end, from data preparation through deployment.
- Production LLM application work (RAG pipelines, agents, or evaluation harnesses).
- Experience with Databricks ETL, data ingestion, or BI and AI workloads on a governed data platform.
Responsibilities
- Design, develop, and deploy AI solutions - search, summarization, agentic automation, AI-assisted decision support - built as reusable components and workflows that scale across use cases.
- Build the data pipelines that analysis and AI solutions depend on.
- Take work from notebook to production, with documented methods, data lineage, and clear ownership.
- Build statistical and machine learning models, and evaluate them honestly, including where they fail.
- Partner with cross-functional stakeholders to turn ambiguous problems into structured solutions with measurable outcomes.
- Build dashboards and applications in Tableau and Power BI that decision makers actually use, and present findings to business and executive audiences.
Benefits
- Supportive work culture that encourages learning, development, and career growth.
- Comprehensive benefits package.
- Eligibility for other forms of compensation such as participation in a bonus and a stock award program, as applicable.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
