Data Analyst

SUMMARY:
Our client is looking for a detail-oriented and analytical Data Analyst to join our team in Pretoria. The ideal candidate will be responsible for collecting, processing, and analyzing data to provide actionable insights that drive business decisions. This role requires a strong understanding of data analysis tools, statistical methods, and data visualization techniques. If you are passionate about turning raw data into meaningful insights, we want to hear from you!

POSITION INFO:

Qualifications:

• Education: Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
• Experience: 2+ years of experience in data analysis or a similar role.
• Certifications (Preferred):
  
  • Microsoft Certified: Data Analyst Associate
  • Tableau Desktop Specialist
  • Google Data Analytics Professional Certificate
  • AWS Certified Data Analytics – Specialty
• Technical Skills:
  
  • Proficiency in data analysis and visualization tools.
  • Strong knowledge of SQL and database management.
  • Experience with statistical analysis and predictive modeling.
  • Familiarity with data cleaning and preprocessing techniques.

Technical Stack:

• Data Analysis Tools: Python (Pandas, NumPy, SciPy), R, SQL
• Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, ggplot2
• Database Management: MySQL, PostgreSQL, Microsoft SQL Server
• Big Data Tools: Hadoop, Spark (optional)
• Statistical Analysis: Regression analysis, hypothesis testing, clustering, and forecasting
• ETL Tools: Apache NiFi, Talend, or similar
• Cloud Platforms: AWS, Azure, or Google Cloud (optional)
• Version Control: Git, GitHub/GitLab

Key Responsibilities:

• Data Collection and Cleaning: Gather data from various sources, clean and preprocess it to ensure accuracy and consistency.
• Data Analysis: Perform exploratory data analysis (EDA) to identify trends, patterns, and insights.
• Reporting: Create and deliver clear, concise reports and dashboards to stakeholders using data visualization tools.
• Predictive Modeling: Develop and implement statistical models to forecast trends and support decision-making.
• Collaboration: Work closely with cross-functional teams, including business analysts, developers, and managers, to understand data needs and deliver solutions.
• Data Governance: Ensure data integrity, security, and compliance with relevant regulations.
• Tool Maintenance: Maintain and optimize data analysis tools and workflows for efficiency.
• Insight Generation: Translate complex data findings into actionable business recommendations.