Trainee / Executive, Data Analyst
Cogdual Infotech Solutions
Role: Trainee / Executive - Data Analyst
Location: Madurai (On-site)
About the Role
The Trainee / Executive – Data Analyst role is a full-time, on-site position. In this role, you will collect, clean, and organize data from multiple sources, then analyze it to identify trends, patterns, and actionable insights. You will prepare reports and dashboards, assist in building data models, and support decision-making with clear visualizations and summaries. You will collaborate with cross-functional teams to understand business requirements, communicate findings, and contribute to ongoing process improvements. The role also involves learning and applying best practices in data analytics tools and methodologies under guidance from senior team members.
Key Responsibilities
- Collect, clean, and organize data from multiple sources.
- Analyze data to identify trends, patterns, and actionable insights.
- Prepare reports and dashboards.
- Assist in building data models.
- Support decision-making with clear visualizations and summaries.
- Collaborate with cross-functional teams to understand business requirements.
- Communicate findings effectively.
- Contribute to ongoing process improvements.
- Learn and apply best practices in data analytics tools and methodologies.
Requirements & Tech Stack
- Analytical Skills
- Foundation in Data Analytics
- Knowledge of Statistics and experience applying statistical concepts.
- Skills in Data Modeling
- Understanding of database or structured data concepts.
- Communication skills for presenting insights.
- Ability to learn quickly and pay attention to detail.
- Ability to work collaboratively in an on-site team environment.
Beneficial Qualifications:
- Proficiency in Excel or spreadsheets.
- Familiarity with data visualization tools (e.g., Power BI, Tableau).
- Basic knowledge of SQL or a programming language used in analytics (such as Python or R).
Qualifications
- A bachelor’s degree in a quantitative, technical, or related field (such as Engineering, Computer Science, Mathematics, Statistics, or Economics) is preferred.
- Internships or academic projects in data-related domains are an added advantage.