AI Data Science Intern, MS - Summer 2027

Marvell Technology•Santa Clara, CA

4d•Hybrid

About The Position

The Data Office, part of Marvell’s CIO organization, builds the company’s data and analytics foundation across supply chain, finance, engineering, sales, and operations. The team develops data pipelines using platforms such as Databricks, Snowflake, and Power BI, and creates trusted datasets, dashboards, machine learning models, and AI agents. Interns contribute to production projects used by teams across the company, with a technical mentor and regular team reviews and feedback. This is a hybrid role. The intern will build data pipelines, develop and deploy machine learning models and AI applications, analyze datasets, create business-facing dashboards, and document and present project findings. The internship is intended for a student pursuing a relevant master’s degree with an expected graduation date between Fall 2027 and Summer 2028. Expected base pay is $32–$63 per hour. Starting pay depends on job-related skills, experience, qualifications, work location, and market conditions. Additional compensation may be available for intern PhD candidates. Intern benefits include medical, dental, and vision coverage, perks and discounts, mental health resources, and paid holidays. Applicants must be eligible to access export-controlled information under applicable law; some applicants may be subject to an export license review process prior to employment.

Requirements

Currently pursuing a master’s degree in Data Science, Computer Science, Statistics, Data Engineering, or a related field, with an expected graduation date between Fall 2027 and Summer 2028.
Proficiency in Python for data processing, analysis, and modeling, using tools such as pandas, NumPy, and scikit-learn.
Strong SQL skills for querying, transforming, and modeling large datasets.
Understanding of data engineering fundamentals, including ETL/ELT design, data warehousing, data modeling, and pipeline orchestration concepts.
Solid foundation in statistics, machine learning, and exploratory data analysis, with familiarity with modern AI models such as LLMs.
Ability to communicate technical findings clearly to technical and non-technical audiences.
Must be eligible to access export-controlled information as defined under applicable law; applicants may be subject to an export license review process.

Nice To Haves

Hands-on experience with data platforms and tools such as Databricks, Snowflake, Spark/PySpark, Delta Lake, Airflow, or dbt.
Experience building dashboards and reports in Power BI, Tableau, or similar BI tools.
Hands-on experience building AI applications with LLMs and agentic frameworks such as LangChain, LangGraph, or similar, including RAG, prompt engineering, and tool integrations such as MCP.
Prior project, internship, or research experience in data engineering or data science.
Familiarity with cloud platforms such as AWS or Azure and with Git/CI/CD.

Responsibilities

Build and maintain scalable ETL/ELT data pipelines in Databricks and Snowflake to ingest, clean, and transform enterprise-system data, including automated data quality checks.
Develop, evaluate, and deploy machine learning models and AI applications, including LLM-based and agentic workflows, to address business problems in areas such as supply chain, engineering productivity, or finance.
Analyze large, multi-source datasets to identify trends, anomalies, and opportunities for improvement, and define metrics to measure them.
Design interactive dashboards and visualizations in Power BI to communicate insights to business stakeholders.
Document pipelines and models, and present findings and recommendations to the mentor, Data Office team, and business partners at the end of the internship.