01Key Responsibilities
- Collect, clean, and analyze large datasets to identify trends and business opportunities.- Build interactive dashboards and reports using tools like Tableau, Power BI, MS Excel.- Perform ad-hoc data analysis to support business and product teams.- Develop and monitor KPIs to track performance across business functions.- Collaborate with engineering teams to define data pipelines and ensure data quality.- Create and present data stories that simplify complex findings for non-technical stakeholders.- Contribute to predictive modeling, segmentation, and automation initiatives using Python or SQL.
02Requirements
- Bachelors degree in engineering, Computer Science, Statistics, or related field.- Strong proficiency in SQL and PostgreSQL for complex queries and data manipulation.- Advanced skills in Python for data analysis and automation, including libraries such as Pandas, NumPy, and Scikitlearn.- Expertise in data visualization tools like Tableau or Looker for creating meaningful dashboards.- Experience with data cleaning, feature engineering, and analytics workflows.- Strong understanding of statistical methods and data validation techniques.- Knowledge of cloud platforms such as Google Cloud Platform (GCP) or AWS is an advantage.Nice to Have:- Experience in marketing analytics, campaign measurement, and customer journey analysis.- Experience working with fintech or financial data is a plus.- Excellent analytical thinking, communication, and storytelling abilities.- Exposure to machine learning techniques.- Knowledge of Python API frameworks or workflow automation tools (e.g., Airflow) is a plus. .
