Location: Nanuet, New York, United States
We are partnered with an innovative company driving the revolution in the loT space. Their mission is improving the efficiency of current manufacturing processes and enabling the next generation of manufacturing through effective gathering, analysis, and productionization of data and insights.
Day to Day
As a Data Scientist you will be responsible for building statistical and machine learning models that improve the efficiency of manufacturing using telemetry collected from the company’s factory cloud. This includes real-time metrics that capture various properties of the manufacturing process, context about these metrics provided from external systems and human input, and offline measurements that describe the quality of the resulting products. Your responsibilities may include:
- Interacting with customers to understand and pose relevant data analysis problems.
- Developing and validating models and methods that address these problems, and working with the engineering team to deploy these as solutions
- Generalizing solutions and innovating to create the next generation of product features
- Engaging with the technical community to present results externally, keep up to date on recent advances, and advance the state of the art
- 6+ years of professional experience as a Data Scientist or
- advanced degrees (M.S. or PhD. in Statistics, Data Science, Computer Science with ML focus, or related fields)
- Experience with Python and SQL
- Experience with designing, building and deploying performant statistical models on large data sets (bonus: experience with time series data, with real-time data analysis)
- Familiarity with process improvement and exploratory techniques (e.g. design of experiments and optimization)
- Enthusiasm to own projects end-to-end; from experimentation to customer delivery
- Experience predictive modeling or machine learning on large datasets (bonus: experience with image data and deep learning)
Complete the form below to apply for the Data Scientist role: