About the job
SummaryBy Outscal
About the job
Urbint uses AI and the latest industry science to identify threats to workers and infrastructure to stop safety incidents before they happen. We are a tight-knit team working together to build powerful technology that prevents serious injuries and infrastructure damages. Many of the largest energy and infrastructure companies in North America trust Urbint to protect workers, assets, communities, and the environment.
Job Summary
As a Data Scientist II, you will be part of the Product Risk Operations team that owns the development of Urbint’s AI-powered technology that helps our clients make communities safer and more resilient. Our technology helps our customers in reducing carbon emissions, reducing infrastructure risk and avoiding fatalities, a fact that we pride ourselves in.
As a part of the Risk Operations team, you will be working on a wide range of activities related to end-to-end Machine Learning (ML) deployments, research and development of ML product features to support internal and external stakeholders. This is a great role for someone who enjoys variety and is also looking to expand their skill set in a structured fashion.
What You’ll Do
- Become a subject matter expert on Urbint’s products, including understanding how AI can be used in the utilities industry to enable our clients desired outcomes.
- Work closely with cross-functional teams to identify opportunities, design experiments and deploy repeatable and scalable machine learning solutions that drive business impact.
- Lead design of experiments and hypothesis tests related to machine learning product features development.
- Lead design, implementation, and deployment of machine learning models to support existing as well as new customers.
- Communicate findings and recommendations to both technical and non-technical stakeholders through clear visual presentations.
- Monitor and analyze machine learning model performance and data accuracy.
- Mentor junior staff members.
- Stay current with best practices in data science, machine learning and AI.
- 3-5 years of experience building and deploying machine learning models
- Master’s or PHD in statistics, mathematics, computer science or another quantitative field
- Strong problem solving skills with emphasis on product development.
- Well versed in programming languages such as R or Python with experience using libraries such as pandas, scikit-learn, tensor flow .
- Experience with SQL and relational databases for data extraction and manipulation.
- Experience using a variety of Machine Learning techniques for Predictive Modeling, Classification, Natural Language Processing (including Large Language Models), Content Recommendation Systems, Time Series Techniques
- Passionate about being up-to-date with the latest developments in Machine Learning
- Strong organizational, time management, and communication skills
- High degree of accountability
- Utility, Infrastructure or Energy related field experience is a plus
About The Company
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