We are looking for talented freshers to join our Data Analytics team based in Ernakulam. .
As a Data Analytics Intern, you will help in gathering, organizing, and analyzing large datasets related to our business. You will be responsible for developing data models that can be used to improve performance of our products.
In this role, your main duties and responsibilities will include, but are not limited to:
• Gather and organize data from multiple sources.
• Develop scripts and programs to clean and transform raw data into usable formats.
• Utilize data mining techniques and analytical methods to identify trends and correlations between data points.
• Apply mathematical, statistical, and predictive modeling techniques to extract insights from data.
• Develop and maintain machine learning models and algorithms to optimize decision-making processes and identify opportunities.
• Create visualizations and reports to communicate results to stakeholders.
• Utilize data cleaning tools such as SQL, Python, R, and other languages to clean data.
• Ensure accuracy of data inputs and outputs.
• Work closely with the product team to analyze user behavior and identify improvement areas.
• Stay up to date on current trends and best practices in data science, machine learning, and AI.
Qualifications:
• Bachelor's degree in computer science, information technology, mathematics, statistics, or a related field.
• Strong understanding of data structures and algorithms.
• Experience with SQL, Python, R, or similar languages.
• Knowledge of data mining techniques and machine learning algorithms.
• Familiarity with big data technologies such as Hadoop, Apache Spark, and Cassandra.
• Excellent communication and presentation skills.
• Ability to work independently and as part of a team.
• Analytical and problem-solving skills.
Job Types: Fresher, Internship
Contract length: 3 months
Schedule:
• Day shift
• Monday to Friday
Expected Start Date: 15/06/2024
Job Types: Full-time, Internship
Contract length: 3 months
Pay: From ?10,000.00 per month
Schedule:
• Day shift
• Monday to Friday
Work Location: In person
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