Data Analyst

Data Analyst (H/F) Role Description & Qualifications

A
Data Analyst (H/F)
is responsible for interpreting and analyzing data to support decision-making processes within an organization. They play a key role in transforming raw data into actionable insights that drive business strategies, optimize operations, and identify growth opportunities. This role requires strong analytical skills, proficiency with data analysis tools, and the ability to communicate findings clearly to both technical and non-technical stakeholders.

Key Responsibilities:

1. Data Collection & Management
   : Collect, clean, and organize data from various sources to ensure accuracy and consistency. This may include extracting data from databases, spreadsheets, cloud systems, or external sources.
2. Data Analysis
   : Analyze large datasets using statistical techniques and analytical methods to uncover trends, patterns, and relationships that are relevant to business objectives.
3. Reporting & Visualization
   : Create visualizations (e.g., charts, graphs, dashboards) and reports to present data in a clear, easy-to-understand format. Tools such as Tableau, Power BI, or Excel are often used for this purpose.
4. Support Decision-Making
   : Provide data-driven insights to inform business strategies and operational decisions. Collaborate with cross-functional teams to understand their data needs and offer recommendations based on analysis.
5. Performance Monitoring
   : Monitor key performance indicators (KPIs) and track business metrics. Analyze deviations from expected trends and provide explanations to stakeholders.
6. Data Quality Assurance
   : Ensure the integrity, accuracy, and security of data. Perform data validation, reconciliation, and regular audits to ensure data is error-free.
7. Continuous Improvement
   : Stay up-to-date with the latest data analysis tools, techniques, and trends. Suggest improvements in data collection, analysis, and reporting processes.

Qualifications:

1. Educational Background
   : A
   Bachelor's degree
   in
   Data Science
   ,
   Statistics
   ,
   Mathematics
   ,
   Economics
   ,
   Computer Science
   , or a related field is generally required. Certifications in data analysis or related fields can be a plus.

2. Technical Skills
   :

3. Strong proficiency in
   Excel
   for data manipulation and analysis.

4. Experience with
   SQL
   to query and manage data from relational databases.
5. Knowledge of data visualization tools like
   Power BI
   ,
   Tableau
   , or
   Google Data Studio
   .

6. Familiarity with data analysis tools and programming languages such as
   Python
   or
   R
   is a strong asset.

7. Analytical Thinking
   : Ability to think critically and use statistical methods to identify trends, patterns, and insights from data. Strong problem-solving abilities are essential.

8. Communication Skills
   : Ability to present complex data insights in a clear and concise manner to stakeholders at all levels. Strong written and verbal communication skills are required for reporting and presenting findings.
9. Attention to Detail
   : Precision and accuracy in data handling, analysis, and reporting. Ability to spot inconsistencies and ensure data integrity.
10. Business Acumen
    : Understanding of business processes and the ability to translate data analysis into practical business recommendations. An understanding of the industry in which the organization operates is beneficial.
11. Teamwork
    : Ability to collaborate effectively with colleagues from various departments, including IT, marketing, finance, and operations.
12. Experience
    : While previous experience in a data analysis role is beneficial, entry-level candidates with strong academic backgrounds and a passion for working with data may also be considered.
13. Adaptability
    : Willingness to learn new tools, technologies, and methodologies as business needs evolve. The ability to quickly adapt to changing environments is key.

Ideal Candidate:

• The ideal
  Data Analyst (H/F)
  is analytical, detail-oriented, and proficient in transforming raw data into valuable insights that drive business decisions. They are technically skilled, with a strong grasp of statistical analysis, data visualization, and reporting tools. In addition, they possess excellent communication skills to effectively present data findings and collaborate with stakeholders across the organization. A strong understanding of business and industry-specific challenges will help them make an impact and add value to the team.