Sr. Data Scientist

Overview

Leads data science initiatives to optimize construction planning, forecasting, and safety.

Key Responsibilities

• model development
• performance monitoring
• data analysis
• predictive modeling
• process optimization
• reporting

Tasks

-Develop and deploy models: Build, test, and deploy machine learning and AI models to improve operational processes. -Performance monitoring: Implement data quality checks and monitor the performance of models and automated systems, creating feedback loops for continuous improvement. -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. -Communicate findings: Present findings and recommendations to stakeholders through reports, visualizations, and presentations. -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. -Reporting and communication: Create dashboards and reports that clearly communicate performance trends and key insights to leadership and other stakeholders. Translate complex data into actionable recommendations. -Analyze operational data: Examine data related to projects, production, supply chains, inventory, and quality control to identify patterns, trends, and inefficiencies. -Collaboration: Partner with project managers, engineers, and business leaders to ensure data solutions are aligned with organizational goals and deliver tangible improvements. -Experimentation: Design and evaluate experiments to quantify the impact of new systems and changes on operational outcomes.

Requirements

• sql
• python
• azure
• aws
• power bi
• generative ai

What You Bring

-Expertise in SQL for data querying and manipulation, and experience with data visualization tools (e.g., Power BI, Tableau). -Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field. -Hands-on experience with Generative AI tools and libraries. -7+ years of experience in data science roles within AEC, product or technology organizations. -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). -Experience working with construction-related data or similar industries (e.g., engineering, manufacturing) is a plus. -Ability to build relationships with diverse stakeholders and cultivate strong partnerships. -Continuous Learning: Stay current with advancements in data science and machine learning to continually enhance the company's data capabilities. -Background in experimentation infrastructure or human-AI interaction systems. -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. -Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies. -Knowledge of time-series analysis, anomaly detection, and risk modeling specific to construction environments. -Solid understanding of statistical methods, predictive modeling, and optimization techniques. -Proven experience designing and interpreting experiments and making statistically sound recommendations. -Familiarity with construction management software (e.g., ACC, Procore, BIM tools) and knowledge of project management methodologies. -Strategic and impact-driven mindset, capable of translating complex business problems into actionable frameworks. -At least 4 years of experience working with cloud platforms, specifically Azure and AWS, for model deployment and data management.

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About Dpr Construction

-A forward-thinking construction company that has grown from a small operation to a nationwide leader in the industry. -Focuses on complex, large-scale projects and is known for its expertise in delivering innovative, high-quality construction solutions. -Successfully completed projects across a range of sectors, including commercial, healthcare, education, and data centers, standing out for its ability to manage large budgets and tight schedules. -Notably completed several landmark projects, including high-tech facilities and cutting-edge educational buildings, often involving collaboration with some of the largest tech and medical organizations in the world. -Strong track record in renewable energy, particularly in solar and energy-efficient construction, positioning them as a leader in sustainable building practices. -Approach to construction is driven by technology and innovation, consistently pushing boundaries to ensure maximum efficiency and quality in its operations. -Commitment to performance and safety has earned a reputation for delivering projects that meet and exceed client expectations. -From healthcare campuses to advanced research labs, the company’s dedication to excellence ensures each project is tailored to the unique needs of the client and the community.

Sector Specialisms