Job Purpose

The primary purpose of a Data Analyst is to extract meaningful insights from data sets, enabling organizations to make informed decisions. This role involves collecting, organizing, and analyzing large volumes of data to identify trends, patterns, and correlations that drive business strategies, optimize processes, and solve problems. Data Analysts also create reports, visualizations, and dashboards to communicate findings effectively to stakeholders and collaborate with teams such as business development, marketing, and operations to provide analytical support.

Roles & Responsibilities

1. Data Collection and Cleaning

• Collect data from various sources (databases, spreadsheets, APIs, etc.).
• Clean and preprocess data to ensure accuracy, completeness, and consistency.

2. Data Analysis

• Conduct exploratory data analysis (EDA) to understand data characteristics.
• Apply statistical techniques and algorithms to extract insights.
• Identify trends, patterns, correlations, and anomalies.
• Perform predictive analysis and modeling for forecasting.

3. Data Visualization and Reporting

• Create charts, graphs, and dashboards to present insights.
• Design and develop reports for stakeholders.
• Ensure visualizations are clear, informative, and aligned with business objectives.

4. Data Interpretation and Recommendations

• Translate analysis results into actionable recommendations.
• Collaborate with stakeholders to understand needs and provide insights.
• Support decision-making with relevant data.

5. Database Management and Querying

• Manage databases ensuring integrity and security.
• Write SQL queries for data retrieval and manipulation.
• Optimize database performance.

6. Continuous Learning and Improvement

• Stay updated with latest tools, technologies, and best practices in data analytics.

Qualifications

• Bachelor’s degree in a related field (Statistics, Mathematics, Computer Science, Economics, Engineering, or IT).

Experience

• 3 to 5 years in data analysis or related roles.

Technical Skills

• Proficiency in programming languages (Python, R, SQL).
• Strong knowledge of statistical analysis techniques.
• Experience with data visualization tools (Tableau, Power BI, matplotlib/seaborn).