Business Data Analyst (Nnews.com.ua)

A Business Data Analyst is responsible for collecting, analyzing, and interpreting data to provide insights and support decision-making processes within a company. They work with various stakeholders, such as management, marketing, finance, and operations, to understand their data needs and deliver actionable information.

Responsibilities:

1. Data Collection: Gather data from different sources, including databases, spreadsheets, and other systems, ensuring data accuracy and completeness.
2. Data Analysis: Use statistical methods and data analysis tools to extract meaningful insights from large datasets. Identify trends, patterns, and correlations to support business objectives.
3. Reporting: Develop and maintain regular reports and dashboards to communicate key performance indicators (KPIs) and business metrics to relevant stakeholders.
4. Data Visualization: Present data in a clear and visually appealing manner through charts, graphs, and other data visualization techniques.
5. Data Cleaning: Clean and preprocess data to remove errors, inconsistencies, and outliers, ensuring data quality.
6. Data Interpretation: Translate complex data findings into understandable and actionable insights for non-technical stakeholders.
7. Business Recommendations: Provide recommendations based on data analysis to support strategic decision-making and business improvements.
8. Collaboration: Work closely with cross-functional teams to understand their data needs and ensure data-driven solutions are aligned with business goals.
9. Continuous Improvement: Stay up-to-date with industry trends, data analysis techniques, and tools to enhance data analytics capabilities.

Requirements:

1. Education: A bachelor's degree in a relevant field, such as Business, Economics, Statistics, Computer Science, or a related discipline. Some positions may require a master's degree or equivalent experience.
2. Analytical Skills: Strong analytical and problem-solving skills are essential for interpreting data and drawing meaningful conclusions.
3. Technical Proficiency: Proficiency in data analysis tools such as Microsoft Excel, SQL, and data visualization tools like Tableau or Power BI. Knowledge of programming languages like Python or R is also beneficial.
4. Communication: Excellent communication skills to convey complex data insights in a clear and understandable manner to non-technical stakeholders.
5. Business Acumen: Understanding of business processes and objectives to align data analysis with organizational goals.
6. Attention to Detail: Meticulous attention to detail is crucial for accurate data analysis and reporting.
7. Team Player: Ability to work collaboratively with cross-functional teams and stakeholders.
8. Problem Solving: Ability to identify business problems and develop data-driven solutions.