Junior Data Analyst – Graduate (35_CL_43_1)
NoAcademy (by Moyyn)
Πλήρης απασχόληση
Πάτρα
Responsibilities
– Data Collection and Processing: Gather data from primary and secondary sources, clean data to ensure accuracy, completeness, and uniformity.
– Data Analysis: Analyze large datasets to identify underlying trends and patterns. Use statistical tools and methodologies to generate useful business insights.
– Model Development: Assist in developing and refining mathematical models for data analysis. This includes predictive modeling and machine learning algorithms.
– Reporting: Create reports and dashboards to communicate the results of data analysis to the management, highlighting key findings and offering actionable insights.
– Collaboration: Work with different teams such as marketing, finance, and operations to understand their data needs and provide analytical support.
– Continuous Learning: Keep up-to-date with the latest industry trends, tools, and technologies in data science and analytics.
– Problem Solving: Apply problem-solving skills to address business challenges using data-driven approaches.
Requirements
– Analytical Skills: Ability to interpret complex data and turn it into actionable insights.
– Communication Skills: Good communication skills to effectively present data insights to non-technical stakeholders.
– Attention to Detail: High attention to detail with an emphasis on accuracy and quality of data.
– Data Collection and Processing: Gather data from primary and secondary sources, clean data to ensure accuracy, completeness, and uniformity.
– Data Analysis: Analyze large datasets to identify underlying trends and patterns. Use statistical tools and methodologies to generate useful business insights.
– Model Development: Assist in developing and refining mathematical models for data analysis. This includes predictive modeling and machine learning algorithms.
– Reporting: Create reports and dashboards to communicate the results of data analysis to the management, highlighting key findings and offering actionable insights.
– Collaboration: Work with different teams such as marketing, finance, and operations to understand their data needs and provide analytical support.
– Continuous Learning: Keep up-to-date with the latest industry trends, tools, and technologies in data science and analytics.
– Problem Solving: Apply problem-solving skills to address business challenges using data-driven approaches.
Requirements
– Analytical Skills: Ability to interpret complex data and turn it into actionable insights.
– Communication Skills: Good communication skills to effectively present data insights to non-technical stakeholders.
– Attention to Detail: High attention to detail with an emphasis on accuracy and quality of data.
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