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Data
Data Intern
You will use various methods to transform raw data into useful data sources, marts etc and ultimately align data systems with business goals. You will need to have strong analytical skills coupled with a keen interest in data analysis and the ability to combine data from different sources.
Data Analysis: Collect, process, and analyze large datasets to extract meaningful insights and identify trends.
Model Development: Develop, implement, and optimize machine learning models and algorithms to solve specific business problems.
Data Visualization: Create clear and compelling data visualizations to communicate findings to stakeholders and support decision-making.
Collaboration: Work closely with cross-functional teams, including data analysts, software engineers, and business stakeholders, to understand requirements and deliver solutions.
Data Engineering: Design and build scalable data pipelines and ETL processes to ensure data is readily available for analysis.
Performance Monitoring: Monitor and evaluate the performance of data models and pipelines, making improvements as needed to ensure accuracy and efficiency.
Research: Stay updated with the latest advancements in data science, machine learning, and artificial intelligence to incorporate best practices and new techniques.
Remote / Work from home
Location:
€40 - €80/hours
Salary:
Job Type:
Part Time or Full Time
Benefits
Daily Income: From $80 to $200
Eligible: For basic salary (excluding daily income)
Training: Comprehensive training to help you develop your data optimization skills.
Growth Opportunities: Potential for career advancement within the company.
Flexible Hours: 1-2 hours per day
Remote Work: Opportunity to work remotely
Supportive Environment: Work in a collaborative and supportive team environment.
Requirements
No experience required.
Able to perform the task independently with minimum supervision.
Reliable internet connection for communication and reporting.
Ability to follow detailed instructions and procedures.
Strong attention to detail and commitment to quality.
Excellent time management skills, attention to detail and the ability to multitask.
Solid understanding of statistical methods and machine learning concepts.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.