Role & Responsibilities :

1. Data Analysis & Insights :

- Analyze large, complex datasets to identify trends, patterns, and actionable insights.

- Perform exploratory data analysis (EDA), statistical modeling, and hypothesis testing.

- Develop dashboards, reports, and data visualizations for business teams.

2. Business Problem Solving :

- Work closely with cross-functional teams (product, engineering, marketing, finance) to understand business goals.

- Convert business questions into analytical problems and deliver data-driven recommendations.

3. Data Management :

- Design, maintain, and optimize data pipelines and ETL processes.

- Ensure data quality, accuracy, and consistency across multiple systems.

4. Reporting & Dashboarding :

- Build interactive dashboards using tools like Tableau, Power BI, Looker, Qlik.

- Automate recurring reporting processes to improve efficiency.

5. Collaboration & Stakeholder Communication :

- Present insights clearly to leadership and non-technical stakeholders.

- Work with data engineers, data scientists, and product teams on data initiatives.

6. Advanced Analytical Work :

- Work on forecasting, segmentation, A/B testing, and cohort analysis.

- Perform SQL optimization and complex query development.

7. Compliance & Best Practices :

- Ensure data privacy, governance, and documentation are maintained.

- Implement analytics best practices and contribute to data strategy.

Preferred Candidate Profile :

1. Experience :

- 5 to 10 years of hands-on experience in data analysis, reporting, and analytics.

- Experience in technology, finance, consulting, retail, healthcare, or similar industries is preferred.

2. Technical Skills :

- Advanced SQL (must-have).

- Strong proficiency in Python or R for data manipulation and analysis.

- Experience with BI tools: Tableau, Power BI, Looker, Qlik.

- Familiarity with databases: Snowflake, BigQuery, Redshift, PostgreSQL, MySQL.

- Experience with ETL tools like Airflow, DBT, Informatica, etc.

3. Analytical Abilities :

- Strong statistical knowledge (regression, probability, distributions).

- Experience with data modeling, forecasting, A/B testing, segmentation.

4. Soft Skills :

- Excellent communicationable to simplify complex data for non-technical teams.

- Strong problem-solving and critical thinking skills.

- Ability to work independently and in cross-functional teams.

5. Education :

- Bachelors or Masters degree in Data Science, Statistics, Computer Science, Economics, Mathematics, or related field.

6. Bonus Skills :

- Experience with AI/ML basics, predictive modeling.

- Cloud platforms: AWS, GCP, Azure.

- Experience with version control (Git) and Agile workflows.