Website Raven Telemetry Inc.
Artificial Intelligence for Manufacturing
Here at Raven Telemetry, we are focused on improving manufacturing worldwide. The Raven platform helps manufacturers collect, interpret and take action on the data being generated in their plants and on their assembly lines and ultimately drives these companies to better manage their manufacturing operations, improve productivity, eliminate waste and increase profitability. Raven’s platform is revolutionizing manufacturing operations management by leveraging the latest in artificial intelligence, advanced data science, IIOT, lean manufacturing principles as well as cloud and mobile computing.
Raven is currently looking for smart, passionate, and hard-working engineers to help us build out our suite of manufacturing analytics and data reporting tools. It takes all types of people to change manufacturing. We welcome and encourage applicants from all stages of their career to apply.
As a data engineer, you will help develop data streams and delivery systems to allow our data science, development, and product teams to operate with real-time data from customers. You will assist our data science team with programming-intensive tasks, and assist our product team with data-intensive tasks. The right candidates will be excited to optimize and help design our company’s data architecture to support our current and next generation products.
- Strong programming skills (we work mostly in Python)
- Expertise in SQL
- Experience in monitoring and automated reporting
- Strong communication skills and the ability to articulate complex ideas and concepts
- An obsession with quality code and overall work
- B.Sc., M.Sc. or equivalent in any computational discipline, e.g. computer science, statistics, mathematics, electrical/computer engineering
- Strong understanding of statistical modeling and inference, data mining, machine learning, and/or AI
- Familiarity with TensorFlow, scikit-learn, Pandas, D3, or similar
- Understanding of microservices, containerization, and modern infrastructure approaches