Marvell Technology is a leader in semiconductor solutions that drive data infrastructure across various sectors. They are seeking a Data Science Intern to support their Data Analytics Team, where the intern will collaborate with data scientists to develop insights and predictive models that address business challenges.
Responsibilities
Collaborate with the data science team to gather, clean, and preprocess data from various sources
Perform exploratory data analysis (EDA) to identify patterns, trends, and relationships within large datasets
Assist in building and optimizing machine learning models to solve business problems
Develop data visualizations, dashboards, and reports using tools like Power BI or Python libraries
Present findings and recommendations to stakeholders in a clear and concise manner
Work with large-scale data sets using SQL, Python for data manipulation and analysis
Support the development and deployment of machine learning models in production .Support data integration and data engineering activities, including ETL processes, within Snowflake or Databricks environments
Qualification
Required
Pursuing degree in Computer Science, Data Science, or related field
Proficiency in Python for data analysis, including libraries like pandas, NumPy, scikit-learn, and matplotlib etc
Knowledge of SQL for querying databases
Understanding of basic statistical concepts and machine learning algorithms (e.g., regression, classification, clustering)
Familiarity with data visualization tools such as Power BI or Python-based visualization libraries (e.g., seaborn, Plotly)
Proficiency in data preprocessing, data transformation, and exploratory data analysis (EDA) to extract valuable insights from raw datasets
Familiarity with Generative AI and Large Language Models (LLMs) is a plus
Preferred
Benefits
Medical, dental and vision coverage
Perks and discount programs
Wellness & mental health support including coaching and therapy
Paid holidays
Paid volunteer days
Paid sick time
Additional compensation may be available for intern PhD candidates.
We believe that infrastructure powers progress. That execution is as essential as innovation. That better collaboration builds better technology.
