Data Scientist

About Buildots

Buildots is transforming construction management with AI and computer vision.

Our AI-powered SaaS platform automates on-site progress tracking, giving construction teams the tools to plan smarter, improve efficiency, and cut costly delays by up to 50%. The $13 trillion construction industry has seen little disruption in the past 150 years. Until now. Backed by leading VCs and industry pioneers, Buildots enables a new, performance-driven approach.

Deployed on hundreds of projects across North America, Europe and the Middle East, Buildots is already reshaping the future of the world's largest industry, and we're on track for rapid expansion in 2025.

Buildots customers include top global contractors, consultants and owners – Intel, Tidhar, Azrieli Group, VINCI Construction, Turner and Multiplex, to name a few.

About the Role

Our Algorithms team tackles the company’s most pressing ML challenges, addressing real-world problems that have a direct impact on success. As part of this group of experienced, you will help establish a new research area within the company, uncovering insights and detecting anomalies that enhance the product’s overall performance.

What You'll Do:

• End-to-end ownership: Identify and frame ambiguous business problems, set measurable success criteria, prototype solutions, and deliver production-ready algorithms.
• Algorithm design: Develop and refine methods across clustering, graph learning, causal inference, time-series modeling, and optimization to enable new product capabilities.
• Workflow deep dive: Work closely with Product teams to analyze current pipelines, map data and decision flows, and identify inefficiencies and opportunities for improvement.
• Real-world data modeling: Explore, structure, and model construction-related data, including progress histories and schedules. Build robust datasets and meaningful features.
• Collaborate with a dynamic team of talented researchers driving digital transformation in the construction industry.

Requirements:

• Adaptability to thrive in a fast-paced startup environment.
• 4+ years of experience solving algorithmic problems with real-world data in areas such as: Unsupervised learning & clustering, Time-series analysis, Graphs & sequences (graph algorithms, path analysis, community detection)
• Strong proficiency in Python (Pandas, NumPy, scikit-learn).
• Skilled in handling complex and noisy datasets.
• BSc in CS, electrical engineering or similar degrees
• Strong product intuition and communication skills: capable of collaborating with diverse teams, translating qualitative challenges into quantitative problem definitions, and clearly articulating trade-offs.

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