Senior Data Scientist

Were looking for a Senior Data Scientist to join Procores Fintech Risk Advisory Team. In this role, youll enable Procore to make smarter, more data-driven decisions, and provide prescriptive solutions to some of Construction's largest problems, particularly focused around how data can help contractors operate safer and drive better insurance outcomes. Construction impacts the lives of nearly everyone in the world, and yet it's also one of the world's least explored industries for how data and AI can impact the industry. Procore has among the largest digital construction data sets in the world. That's why we're looking for talented Data Scientists to join Procore's journey to revolutionize a historically underserved industry. As a Senior Data Scientist, youll partner with the Fintech department to implement the set of services needed to release AI and data science models capable of working with TB of data. You'll model related features including one-time and ongoing automatic model training, deploying, and monitoring models. This position is a great opportunity to use your machine learning, data engineering, and AWS cloud service skills to enable machine learning as a service at scale at Procore. This position reports into the Fintech Director of Actuarial and Data Science and has the opportunity to be located in any of our US offices, or permanently remote within the US or Canada. Were looking for someone to join us immediately. Responsibilities Work with Fintech org to develop and deploy reliable and insightful ML models Provide technical leadership for efforts around tooling and infrastructure that enable teams to complete and maintain AI/ML projects efficiently Partner with cross-departmental teams to understand the business requirements and design user feedback loop to collect user data Coach and mentor junior data scientists on the team; lead code reviews, design, and best practices Participate in the evolution of Data Science at Procore Qualifications 8 years of hands-on experience developing predictive models and managing the machine learning lifecycle: data preprocessing and feature development, model training and evaluation, deployment MS or Ph.D. degree in Mathematics, Computer Science, or a related field is preferred Experience with problem framing across multiple data science and machine learning subdomains, including forecasting, anomaly detection, classification, and regression Superior communication skills with the ability to distill rigorous mathematical and statistical concepts such that non-experts may understand Demonstrable experience launching NLP and CV solutions Demonstrable experience with developing actionable solutions with LLM tools Familiarity with AWS cloud infrastructure services and container systems such as Docker or Kubernetes Familiarity with Python ML packages, deep learning framework (Pytorch or Tensorflow), and computer vision packages Professional experience in software development (software design and development life cycle) preferred J-18808-Ljbffr