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Analog Devices Internship Drive 2025 Details :
Analog Devices Internship Drive 2025 Eligibility Criteria :
Qualifications:
- Pursuing a degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
- Strong foundation in statistics and data analysis.
- Proficiency in Python, R, or similar programming languages for data analysis.
- Familiarity with SQL for querying databases and extracting data.
- Good understanding of data visualization tools (e.g., Tableau, Power BI, or equivalent).
- Eagerness to learn new technologies and analytical methods.
- Strong problem-solving skills and attention to detail.
Preferred Skills (Not mandatory):
- Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.
- Knowledge of data cleaning and transformation techniques.
- Basic experience with cloud platforms (Azure, AWS, or GCP).
- Familiarity with big data tools like Spark is a plus.
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Overview:
We are looking for a passionate Data Analyst/Data Scientist Intern to join our central data team. This role will allow you to apply your analytical and machine learning skills while contributing to our Enterprise Data Platform. You will work alongside data engineers and business stakeholders to derive insights from complex datasets, develop predictive models, and support data-driven decision-making across various business functions.
Responsibilities :
- Analyze large datasets to uncover trends, insights, and patterns that support strategic decision-making.
- Develop dashboards and visualizations to present data insights to business stakeholders using tools like Tableau, Power BI, or similar.
- Collaborate with cross-functional teams to define and solve business problems using data.
- Assist in building and validating predictive models using techniques like regression, classification, and clustering.
- Support in cleaning, transforming, and preparing data for analysis using tools such as SQL, Python, or R.
- Contribute to building machine learning models and help deploy them in a production environment.
- Work on data quality assessments and help ensure that the data used for analysis is accurate and complete.
What You’ll Learn :
- Practical experience in analyzing real-world datasets and solving business challenges using data.
- Exposure to machine learning algorithms and techniques, including model training, validation, and deployment.
- Hands-on experience with data visualization tools and methods to communicate insights effectively.
- How to work with cloud-based data platforms and integrate data science tools into the broader data ecosystem.
- Collaborating in a cross-functional environment with data engineers, analysts, and business teams.
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