Data yst

Key Responsibilities

1. Data Collection and Preparation:

• Gather data from various sources including databases spreadsheets and APIs.
  
• Cleanse and preprocess data to ensure accuracy and consistency.
  
• Structure and organize data to facilitate analysis.
  

2. Data Analysis:

• Utilize statistical techniques and analytical methods to interpret data.
  
• Detect trends patterns and correlations within datasets.
  
• Perform exploratory data analysis (EDA) to uncover insights.
  
• Conduct hypothesis testing and statistical inferences.
  

3. Data Visualization:

• Develop visualizations such as charts graphs and dashboards to communicate insights effectively.
  
• Utilize tools like Tableau Power BI or matplotlib for data visualization.
  
• Create visually compelling and informative reports for stakeholders.
  

4. Reporting and Presentation:

• Compile reports and presentations that summarize findings and insights.
  
• Convey complex technical concepts in a clear and accessible manner.
  
• Present insights to stakeholders including management and nontechnical audiences.
  

5. DataDriven DecisionMaking:

• Collaborate with crossfunctional teams to understand business needs.
  
• Offer datadriven recommendations and insights to support decisionmaking processes.
  
• Monitor key performance indicators (KPIs) and metrics to assess progress and performance.
  

6. Continuous Learning and Development:

• Stay informed about emerging trends tools and technologies in data analysis.
  
• Continuously enhance analytical skills through training certifications and practical experience.
  
• Share knowledge and best practices with colleagues to promote a learningoriented environment.
  

Skills and Qualifications:

• Proficiency in SQL for data querying and manipulation.
  
• Strong analytical and problemsolving abilities.
  
• Experience with statistical analysis and data visualization tools.
  
• Familiarity with programming languages such as Python or R.
  
• Understanding of data warehousing concepts and data modeling.
  
• Excellent communication and presentation skills.
  
• Keen attention to detail and the ability to work independently.
  
• Bachelor s degree in a relevant field such as statistics mathematics computer science or a related discipline. A master s degree or certifications in data analysis or related fields is preferred.