Your impact
We are seeking a Data Analyst/Project Controls professional to support our client on the project site at Pearl Harbor. Work will be full-time onsite.
- You will provide assistance and technical schedule guidance to construction managers and engineering technicians exercising construction oversight and design management for the construction program.
- You will provide comprehensive data analysis services to enhance project oversight, decision-making, and continuous improvement efforts.
- The A-E Data Analyst shall ensure that OICC and project stakeholders have access to timely, accurate, and actionable insights derived from integrated data sources and robust analytical methods.
- Limited but strategic use of AI-driven techniques will be employed to supplement traditional analytics and highlight emerging trends or risks.
Additional Responsibilities:
- Data Integration & Management: Identify and consolidate relevant project data sources (e.g., schedule data, cost reports, quality metrics, BIM/CAD outputs, risk registers) into a unified, secure data environment.
- Metrics & KPIs: Define and track key performance indicators (KPIs) related to project cost, schedule, quality, and other critical areas. Ensure that these metrics accurately reflect project status, progress, and potential improvement areas.
- Analytical Methods & Tools: Apply statistical techniques, data visualization software, and, where beneficial, basic machine learning or AI-driven methods (e.g., anomaly detection, trend forecasting) to uncover insights that inform project decisions.Predictive Analysis & Early Warning Indicators: Use predictive analytics augmented by simple AI models when advantageous to forecast potential delays, budget overruns, or risk events. Provide early warning indicators that enable proactive issue resolution and resource adjustments.
- Visualization & Reporting: Develop interactive dashboards, charts, and periodic reports that present data in clear, accessible formats for both technical and non-technical stakeholders. Visualization tools should highlight trends, variances, and correlations that might otherwise remain hidden.
- Scenario & “What-If” Analysis: Conduct scenario modeling to examine the potential impacts of schedule changes, resource allocations, or cost fluctuations. Integrate select AI-driven pattern recognition techniques to refine scenario outcomes or identify optimal solutions.
- Quality Assurance & Data Governance: Implement data validation checks, version control, and quality assurance measures to ensure data integrity and reliability. Advise on best practices for data governance and compliance with applicable standards and regulations.
- Collaboration & Integration: Work closely with Operation to collaborate independently with Schedule, Risk Management, and other project teams to ensure that analytics outputs are fully integrated into governance briefings, communication protocols, and project workflows.
- Training & Capacity Building: Provide training sessions, reference materials, and guidance to OICC PHNSY personnel, enabling them to interpret data dashboards, understand analytical outputs, and incorporate data-driven insights into their daily operations.
- Continuous Improvement & Technology Adoption: Stay informed about emerging analytical tools, industry best practices, and incremental AI solutions. Recommend pragmatic enhancements to the analytics approach that improve accuracy, efficiency, and stakeholder value over time.
Meeting and Reporting Requirements:
- Monthly Data Analytics Report: Highlights key project metrics, trends, predictive indicators, and improvement recommendations.
- Interactive Dashboards & Visualizations: Regularly updated dashboards presenting KPIs, forecasts, and identified trends in a user-friendly format.
- Ad-Hoc Analysis & Scenarios: On-demand analytical support for scenario testing, “what-if” analysis, and resource planning exercises, incorporating limited AI-driven enhancements as appropriate.
- Training & Reference Materials: Documentation, training aids, and workshop sessions to help personnel effectively leverage data insights and incorporate moderate AI-driven outputs into decision-making processes.
Here's what you'll need
- Bachelors degree in Construction Management, Engineering, or related discipline
- Minimum 5 years of experience in construction and engineering project environment
- US Citizenship required
- Monthly Data Analytics Report: Highlights key project metrics, trends, predictive indicators, and improvement recommendations.
- Interactive Dashboards & Visualizations: Regularly updated dashboards presenting KPIs, forecasts, and identified trends in a user-friendly format.
- Ad-Hoc Analysis & Scenarios: On-demand analytical support for scenario testing, “what-if” analysis, and resource planning exercises, incorporating limited AI-driven enhancements as appropriate.
- Training & Reference Materials: Documentation, training aids, and workshop sessions to help personnel effectively leverage data insights and incorporate moderate AI-driven outputs into decision-making processes.
Ideally you'll also have:
- Work experience on Naval bases and shipyards supporting engineering and construction projects
- Federal project experience working with or alongside NAVFAC
- Experience on drydock projects
