Role & responsibilities :

1. Data Collection & Data Management :

- Gather, clean, and preprocess data from various sources (databases, spreadsheets, APIs, etc.).

- Maintain and organize databases to ensure data is accessible and accurate.

2. Data Analysis :

- Analyze large datasets to identify trends, patterns, and insights that can help with business decision-making.

- Use statistical tools and techniques to interpret data and generate actionable insights.

- Perform data validation to ensure data integrity.

3. Data Visualization :

- Create reports, dashboards, and visualizations (using tools like Excel, Tableau, Power BI, or Python libraries like Matplotlib/Seaborn).

- Present findings clearly to non-technical stakeholders in an easy-to-understand format.

4. Reporting :

- Prepare and present regular reports on business metrics and key performance indicators (KPIs).

- Monitor data trends and provide timely reports on business performance.

5. Collaboration :

- Work closely with different teams (marketing, finance, operations, etc.) to understand business objectives and data needs.

- Provide data-driven recommendations for improvements in business strategies.

Preferred Candidate Profile :

1. Educational Qualifications :

- A bachelor's degree in a relevant field such as Computer Science, Statistics, Mathematics, Economics, or Business Administration.

- Certifications in data analysis, statistics, or data science (e.g., Microsoft Power BI, Google Data Analytics, Tableau, etc.) are a plus.

2. Technical Skills :

- Proficient in Data Analysis Tools : Excel, SQL, R, Python (for analysis), and statistical software.

- Data Visualization : Knowledge of tools like Tableau, Power BI, or advanced Excel techniques for creating charts, graphs, and dashboards.

- Data Management : Understanding of databases (SQL, NoSQL) and ability to extract, clean, and manipulate data.

3. Analytical & Statistical Skills :

- Solid understanding of statistical methods and their application in data analysis.

- Ability to perform exploratory data analysis (EDA), hypothesis testing, and regression analysis.

- Comfort with interpreting and analyzing large and complex datasets.

4. Problem-Solving & Critical Thinking :

- Strong analytical mindset to uncover patterns and provide actionable insights.

- Ability to break down complex problems and analyze them systematically.

- Creative in finding ways to apply data to solve real business challenges.

5. Communication & Presentation Skills :

- Ability to communicate complex data findings to non-technical stakeholders in a simple and clear way.

- Experience in presenting reports and insights to business leaders and executives.

- Strong written and verbal communication skills.

6. Attention to Detail :

- High level of accuracy and attention to detail when working with data and generating reports.

- Ability to spot data inconsistencies, errors, or gaps.

7. Teamwork & Collaboration :

- Ability to work cross-functionally with different teams to gather requirements and deliver insights.

- Strong interpersonal skills and adaptability in a fast-paced, evolving business environment.