Data Scientist II
Job Description
Urbint is Hiring for Data Scientist II
Company Overview: At Urbint, we utilize AI and cutting-edge industry science to proactively identify threats to workers and infrastructure, preventing safety incidents before they occur. Our team is dedicated to developing powerful technology that safeguards workers, assets, communities, and the environment. Trusted by some of the largest energy and infrastructure companies in North America, Urbint is committed to creating safer and more resilient communities.
Job Summary: As a Data Scientist II, you’ll join the Product Risk Operations team at Urbint, responsible for developing our AI-powered technology. This technology aids our clients in making communities safer and more resilient by reducing carbon emissions, infrastructure risk, and fatalities. In this role, you’ll work on a variety of activities related to machine learning deployments, research, and development of product features to support internal and external stakeholders.
What You’ll Do:
- Become an expert on Urbint’s products, understanding how AI benefits the utilities industry.
- Collaborate with cross-functional teams to identify opportunities and deploy scalable machine learning solutions.
- Lead experiments and hypothesis tests related to product feature development.
- Design, implement, and deploy machine learning models for new and existing customers.
- Communicate findings and recommendations to technical and non-technical stakeholders.
- Monitor machine learning model performance and data accuracy.
- Mentor junior team members.
- Stay updated on best practices in data science, machine learning, and AI.
Who You Are:
- 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 a focus on product development.
- Proficient in programming languages like R or Python, with experience in libraries such as pandas, scikit-learn, and TensorFlow.
- Experience with SQL and relational databases for data extraction and manipulation.
- Knowledge of various machine learning techniques for predictive modeling, classification, NLP, content recommendation systems, and time series analysis.
- Passionate about staying updated with the latest developments in machine learning.
- Strong organizational, time management, and communication skills.
- Utility, infrastructure, or energy industry experience is advantageous.