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About the role
Job Responsibilities: Collaborate with project teams and clients to understand business requirements and translate them into analytical solutions (BRD/FRD). Analyze large, complex datasets related to construction projects (Cost, Schedule, Risk, Quality, Safety, etc.) to identify trends, anomalies, and actionable insights. Develop and maintain dashboards and reports using tools like Power BI, Paginated Reports, and Excel to support project decision-making. Perform data validation and quality assurance checks to ensure accuracy and consistency of reports and models. Optimize and maintain data models and ETL processes in collaboration with data engineering teams. Support forecasting and predictive analytics for cost overruns, schedule delays, and risk exposure using statistical tools (e.g., Python, R). Track and report on key project performance indicators (KPIs) and project controls. Communicate findings and recommendations clearly to technical and non-technical stakeholders. Contribute to continuous improvement of data processes and reporting standards. Skills: Technical Skills: Proficiency in Power BI, Power Platform (Power Automate, PowerApps), and Paginated Reports. Strong SQL skills for querying and transforming data from relational databases (SQL Server, Snowflake preferred). Experience with Python or R for statistical analysis and predictive modeling. Familiarity with APIs and ETL processes for data integration. Understanding of data warehousing concepts and transactional systems. Advanced Excel skills for data manipulation and reporting. Domain Knowledge (Construction Analytics) Cost Management: The analyst should possess a strong understanding of construction cost structures and estimating practices to effectively interpret and analyze financial data. Interpret and deconstruct project budgets and estimates into granular cost components. Analyze budget vs. actuals to identify cost overruns and savings opportunities. Develop and maintain data-driven cash flow forecasts by integrating budget data with trade sequencing and project schedules. Collaborate with project controls and finance teams to ensure cost data accuracy and alignment with reporting standards. Track and analyze change orders and their impact on scope, cost, and schedule. Schedule Management: The analyst should understand construction scheduling methodologies and dependencies to accurately assess project timelines and risks. Track Monitor project timelines and milestone progress using scheduling tools like Primavera P6. Identify schedule variances and potential delays through trend analysis and critical path evaluation. Integrate schedule data with cost and resource metrics to support holistic project performance reviews. Quality: The analyst should be familiar with construction quality assurance processes to interpret inspection data and support continuous improvement. Analyze quality inspection data and punch lists to identify recurring issues and trends. Develop KPIs and dashboards to monitor quality performance across projects and contractors. Support root cause analysis and continuous improvement initiatives using data driven insights. Safety: The analyst should understand construction safety protocols and reporting standards to effectively analyze incident data and support risk mitigation. Monitor safety incident data and near-miss reports to identify high-risk activities or locations. Provide visualizations and reports to aid safety audits and compliance tracking. Job Responsibilities: Collaborate with project teams and clients to understand business requirements and translate them into analytical solutions (BRD/FRD). Analyze large, complex datasets related to construction projects (Cost, Schedule, Risk, Quality, Safety, etc.) to identify trends, anomalies, and actionable insights. Develop and maintain dashboards and reports using tools like Power BI, Paginated Reports, and Excel to support project decision-making. Perform data validation and quality assurance checks to ensure accuracy and consistency of reports and models. Optimize and maintain data models and ETL processes in collaboration with data engineering teams. Support forecasting and predictive analytics for cost overruns, schedule delays, and risk exposure using statistical tools (e.g., Python, R). Track and report on key project performance indicators (KPIs) and project controls. Communicate findings and recommendations clearly to technical and non-technical stakeholders. Contribute to continuous improvement of data processes and reporting standards. Skills: Technical Skills: Proficiency in Power BI, Power Platform (Power Automate, PowerApps), and Paginated Reports. Strong SQL skills for querying and transforming data from relational databases (SQL Server, Snowflake preferred). Experience with Python or R for statistical analysis and predictive modeling. Familiarity with APIs and ETL processes for data integration. Understanding of data warehousi