Big Data Analytics Intern
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Stipend: ₹Performance Based
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Full time
Are you passionate about data and eager to dive into the world of Big Data Analytics? Web Neural Infotech is offering an exciting internship opportunity where you will gain hands-on experience with cutting-edge technologies and develop your skills in one
Responsibilities
- Data Collection: Learn to gather and integrate data from various sources such as social media, IoT devices, and transaction records using tools like Apache Kafka, Flume, and Sqoop.
- Data Storage: Understand and manage large datasets efficiently with technologies like Hadoop Distributed File System (HDFS) and NoSQL databases (e.g., MongoDB, Cassandra).
- Data Processing: Work with frameworks such as Apache Hadoop, Apache Spark, and Apache Flink to clean, filter, and prepare data for analysis.
- Data Analysis: Apply statistical, machine learning, and computational techniques to analyze data using tools such as R, Python (Pandas, NumPy), and Apache Spark MLlib.
- Data Mining: Extract patterns and trends from data using techniques and tools like RapidMiner, Weka, and KNIME to uncover deeper insights.
- Data Visualization: Present your analysis results using visualization tools like Tableau, Power BI, D3.js, and Apache Superset to help stakeholders understand the insights
Required Skills/Qualifications
- Data Collection: Learn to gather and integrate data from various sources such as social media, IoT devices, and transaction records using tools like Apache Kafka, Flume, and Sqoop.
- Data Storage: Understand and manage large datasets efficiently with technologies like Hadoop Distributed File System (HDFS) and NoSQL databases (e.g., MongoDB, Cassandra).
- Data Processing: Work with frameworks such as Apache Hadoop, Apache Spark, and Apache Flink to clean, filter, and prepare data for analysis.
- Data Analysis: Apply statistical, machine learning, and computational techniques to analyze data using tools such as R, Python (Pandas, NumPy), and Apache Spark MLlib.
- Data Mining: Extract patterns and trends from data using techniques and tools like RapidMiner, Weka, and KNIME to uncover deeper insights.
- Data Visualization: Present your analysis results using visualization tools like Tableau, Power BI, D3.js, and Apache Superset to help stakeholders understand the insights
Eligibility Criteria
Educational Background: Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, or a related field.
Coursework or Experience: Prior coursework or practical experience in big data analytics, data processing, and data visualization. Experience with projects involving large datasets and big data technologies is advantageous.
Technical Proficiency: Demonstrated proficiency in using big data frameworks and programming languages for data processing and analysis. Knowledge of SQL and experience with data manipulation in databases is beneficial.
Benefits/Perks
Mentorship and Learning: Receive mentorship from experienced data scientists and engineers, gaining valuable insights into industry practices and advanced big data technologies.
Hands-on Experience: Gain practical experience working with real-world datasets and state-of-the-art big data tools. Develop a strong foundation in big data analytics for business applications.
Professional Growth: Opportunity to enhance technical skills and build a strong portfolio of big data projects. Potential for a full-time position based on performance and organizational needs.
Networking: Engage with professionals across various departments, expanding professional networks and building relationships within the data science and big data communities.
Flexible Working Hours: Enjoy a flexible working schedule that accommodates academic commitments and promotes work-life balance. Option to work remotely or on-site as per project requirements.
Stipend: Competitive stipend to support the intern during the internship period. Financial support for additional learning resources and certification programs.
Access to Resources: Utilize company resources, including training materials, software tools, and industry research, to enhance learning and development. Access to a library of big data and analytics resources.
Company Details
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