Position Description:

The Data Scientist with Plasmatic Technologies is a position that focuses on big data processing of various Smart Home data. A focus should be placed on innovative ways to represent data relationships such that the database can be easily updated when new data is obtained, or when a new relationship is formed. The system must also be tailored for deployment. Proficiency in NodeJS for frontend development is required.

Required Technical Skills:

Applicants should have a graduate degree in mathematics, engineering, computer science, or data science. 
The following technology skills are essential to success:

  • NodeJS

  • NoSQL databases

  • Algorithm design

  • Statistical methods and optimization algorithms

  • Linux OS

  • AWS Development and Management

  • Git and Source code management

  • Troubleshooting and code debugging

Required Characteristics:

We are a collaborative team with a commitment to continued learning, and we love working with technology. Individuals should have an insatiable desire to learn, an eagerness to grow above and beyond their current level of experience, and be great communicators.  
A successful candidate should be able to:

  • Work independently with a focus on deadlines and deliverables within a team context

  • Ability to conduct research in an interdisciplinary environment both independently and as part of a team

  • Proactive in finding new technologies or opportunities that will help move projects forward or improve upon them

  • Perform technology research and presentation of results

  • Independently troubleshoot problems and determine root cause

  • Dive into routine tasks (as we all must at times)

  • Be willing to provide leadership when presented with projects or tasks

  • Work collaboratively across business groups and skillsets

  • Provide energy and encouragement to others with willingness to help others succeed and improve

  • Communicate designs and design suggestions with engineering staff as well as across the company

  • Consider design constraints from multiple points of view (marketing, industrial design, business costs, consumer values)

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