Data science

• Skills in data analysis and programming using various analytical tools such as Python, R, and SQL, with the ability to understand data and extract patterns and trends from it.
• Deep understanding of basic statistical and mathematical concepts used in data analysis, enabling effective application of statistical methods in practical work.
• Ability to analyze and visualize data using visualization tools like Tableau and Power BI, and create reports and illustrative charts for data.
• Communication and collaboration skills, with the ability to present statistical and analytical results effectively to teams and non-specialist colleagues, and explain conclusions and recommendations in a clear manner.
• Deep understanding of data science applications in various fields such as marketing, healthcare, finance, forecasting, and machine learning.

• Business Data Analyst: Responsible for analyzing business and financial data to understand the company’s performance and improve its processes. They analyze data, identify trends, and key insights that contribute to strategic decision-making for the company.
• Digital Marketing Analyst: Uses smart data analysis to understand consumer behavior and measure the effectiveness of digital marketing campaigns. They analyze data from social media platforms and websites to enhance digital marketing strategies.
• Economic Analyst: Analyzes data to understand the overall economy and various industries, using advanced tools to analyze economic and social data, identify trends, and forecast economic conditions.
• Human Resources Performance Analyst: Utilizes modern smart tools to analyze data related to employees and human resources.