Data Analyst

Job Title - Data Analyst

Job Summary:

We are looking for a highly skilled and motivated Data Analyst with hands-on experience in Power BI (DAX), SQL, Python, and advanced analytics. The ideal candidate will play a key role in transforming large and complex datasets related to telecom tower operations and assets into actionable insights, supporting business decisions and predictive analysis across the organization.

Key Responsibilities:

• Design and develop interactive dashboards and reports using Power BI, with strong command over DAX for custom metrics and logic.
• Extract, clean, transform, and analyze large-scale operational data from telecom towers and asset databases.
• Write and optimize SQL queries to retrieve structured data from relational databases for analysis.
• Use Python for data wrangling, statistical analysis, and model development.
• Develop and deploy predictive models using time series forecasting for use cases such as asset failures, energy usage, and maintenance planning.
• Leverage foundation models or AI models to generate advanced analytical solutions for anomaly detection, site performance trends, etc.
• Translate business problems into analytical solutions and present findings with clarity and impact.
• Collaborate with cross-functional teams including operations, product to align on data requirements and analytical insights.

Required Skills & Qualifications:

• Proven experience with Power BI development, including advanced DAX formulas and visual storytelling.
• Strong knowledge of SQL and database.
• Proficiency in Python for data analysis.
• Solid foundation in data analysis, statistics, and data visualization techniques.
• Experience in handling large datasets, especially in telecom or infrastructure domains would be an added advantage.
• Analytical mind set with strong problem-solving skills and a proactive attitude.
• Ability to work independently and in a collaborative team environment.

Advanced Skills:

• Experience in building and deploying AI/ML models, especially foundation models for operations-related analytics.
• Exposure to time series forecasting models (ARIMA, Prophet, LSTM, etc.).