10 дней назад
Data Science Intern
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Science Intern (Data Science/ML): Analyzing structured and unstructured data, preparing datasets, and contributing to models and visualizations that support business decision-making with an accent on exploratory data analysis, data integration, and machine learning. Focus on validating model performance, translating analytical insights into visualizations, and supporting data science solutions.
Location: United States; hybrid work with an average of 2 days per week from an HPE office
Company
is a global edge-to-cloud technology company that helps organizations connect, protect, analyze, and use data and applications.
What you will do
- Analyze and validate datasets, solutions, and user experiences.
- Prepare data for exploratory data analysis and hypothesis development.
- Support metadata development, data loading, data mapping, transfer, and migration.
- Contribute to building, validating, and selecting analytical and machine learning models.
- Research and deliver data science solutions to business problems.
- Visualize model insights and support analytics model configuration tools.
Requirements
- Working toward a Bachelor's or Master's degree in Data Science, Computer Science, Computer Engineering, Software Development, or a related IT field.
- Basic knowledge of data science methodologies, machine learning, data integration, modeling, and data visualization.
- Basic understanding of business requirements, data science objectives, and ETL tools.
- Basic knowledge of analytics software and programming languages, including R, SAS, SPSS, or Python.
- Basic communication and presentation skills.
- Ability to work an average of 2 days per week from an HPE office in the United States.
Culture & Benefits
- Health and wellbeing benefits supporting physical, financial, and emotional wellbeing.
- Personal and professional development programs supporting career growth.
- Inclusive workplace that values varied backgrounds and individual uniqueness.
- Flexible approach to managing work and personal needs.
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