AI Data Science Intern, MS (2603846)
About Marvell
Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities.
At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead.
Your Team, Your Impact
The Data Office, part of Marvell’s CIO organization, builds the data and analytics foundation that helps the company make faster, better decisions across supply chain, finance, engineering, sales, and operations. Our team engineers the data pipelines that bring Marvell’s core enterprise systems together on modern platforms such as Databricks, Snowflake, and Power BI, and turns that data into trusted datasets, dashboards, machine learning models, and AI agents. Our work helps Marvell predict supply risk, improve product development efficiency, and put AI-driven insights in the hands of business leaders. As an intern, you will work on real projects that go into production and are used by teams across the company.
What You Can Expect
- Build and maintain scalable data pipelines (ETL/ELT) in Databricks and Snowflake that ingest, clean, and transform data from enterprise systems, with automated data quality checks
- Develop, evaluate, and deploy machine learning models and AI applications, including LLM-based and agentic workflows, that solve real business problems in areas such as supply chain, engineering productivity, or finance
- Analyze large, multi-source datasets to uncover trends, anomalies, and opportunities for improvement, and define the metrics that measure them
- Design interactive dashboards and visualizations in Power BI that communicate insights to business stakeholders
- Document pipelines and models, and present findings and recommendations to your mentor, the Data Office team, and business partners at the end of your internship
This is a hybrid role. You will be paired with a technical mentor and will meet regularly with the team to review progress and get feedback.
What We're Looking For
- 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 – Summer 2028
- Proficiency in Python for data processing, analysis, and modeling (e.g., pandas, NumPy, scikit-learn), and 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 large language models (LLMs)
- Ability to communicate technical findings clearly to both technical and non-technical audiences
Preferred
- 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 (e.g., MCP)
- Prior project, internship, or research experience in data engineering or data science, with familiarity with cloud platforms (AWS or Azure) and Git/CI/CD