DPR Construction is seeking to advance its data-driven approach to building by turning complex construction and business data into actionable insights that improve project planning, cost forecasting, resource management, and safety.
Requirements
- Strong proficiency in Python or R for data analysis, modeling, and machine learning, with experience in relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and NLP frameworks (e.g., GPT, Hugging Face Transformers).
- Expertise in SQL for data querying and manipulation, and experience with data visualization tools (e.g., Power BI, Tableau).
- Solid understanding of statistical methods, predictive modeling, and optimization techniques.
- Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies.
- At least 4 years of experience working with cloud platforms, specifically Azure and AWS, for model deployment and data management.
- Familiarity with construction management software (e.g., ACC, Procore, BIM tools) and knowledge of project management methodologies.
- Hands-on experience with Generative AI tools and libraries.
Responsibilities
- Data analysis and modeling: Analyze large datasets to identify trends, bottlenecks, and areas for improvement in operational performance. Build predictive and statistical models to forecast demand, capacity, and potential issues.
- Develop and deploy models: Build, test, and deploy machine learning and AI models to improve operational processes.
- Analyze operational data: Examine data related to projects, production, supply chains, inventory, and quality control to identify patterns, trends, and inefficiencies.
- Optimize processes: Use data-driven insights to streamline workflows, allocate resources more effectively, and improve overall performance.
- Forecast and predict: Create predictive models to forecast outcomes, such as demand, and inform strategic decisions.
- Ensure reliability: Build and maintain reliable, scalable, and efficient data science systems and processes.
- Performance monitoring: Implement data quality checks and monitor the performance of models and automated systems, creating feedback loops for continuous improvement.
Other
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
- 7+ years of experience in data science roles within AEC, product or technology organizations.
- Ability to build relationships with diverse stakeholders and cultivate strong partnerships.
- Strong communication skills, including the ability to bridge technical and non-technical stakeholders and collaborate across various functions to ensure business impact.
- Ability to operate effectively in a fast-moving, ambiguous environment with limited structure.
