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Data Science Intern Resume
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What should I put on my resume for Data Science Intern?
Your data science intern resume should highlight your academic background in data science, computer science, statistics, or a related field, as well as any relevant coursework or projects you've completed. Include any experience working with data analysis tools, programming languages, and machine learning, as well as any relevant extracurricular activities or side projects. Additionally, mention any relevant internships or work experience, and any publications, presentations, or awards you've received.
What are the key characteristics of an effective Data Science Intern?
An effective data science intern should have strong analytical and problem-solving skills, and a strong foundation in data science, computer science, statistics, or a related field. They should have experience working with data analysis tools and programming languages, as well as an understanding of machine learning concepts and algorithms. Additionally, they should be able to effectively communicate findings and insights to technical and non-technical stakeholders, and be able to work well in a team environment.
What type of job path can one expect to have as a Data Science Intern?
As a data science intern, one can expect to gain hands-on experience working on real-world data science projects, and build skills in data analysis, programming, and machine learning. This can lead to opportunities in entry-level roles such as data analyst, data engineer, or machine learning engineer. With further education and experience, one may progress to more advanced roles such as data scientist or senior data scientist. Additionally, opportunities exist in various industries such as finance, healthcare, retail, and technology, as well as with consulting firms and data-focused startups.
• New York City, New York • firstname.lastname@example.org • in/cbloomberg
Master of Science in Biology - Data Science focus | New York University | 2020
Machine Learning: Python (scikit-learn, pandas, NumPy), keras, TensorFlow, Pytorch, Spark MLlib
Data Visualization Tools: Tableau, R Studio, Power BI, Latex, Advance Excel