Research Data Scientist
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MachineMetrics was founded by a small group of software and manufacturing professionals unified by a mission to deliver meaningful products that can change the manufacturing world. MachineMetrics has simplified Industrial IoT to digitize the shop floor and enable teams to drive decisions with machine data.
Manufacturing impacts almost every aspect of how we interact with the physical and virtual world today, from the technology we use at work to the way we communicate with each other in our daily lives. Today is the internet moment for manufacturers and MachineMetrics is a pioneer in empowering a more sustainable, resilient, automated factory of the future.
To accomplish this we've combined world-class talent in both advanced manufacturing and cutting edge technology to build a company focused on solving real manufacturing problems. Our work environment is busy, non-political, and comfortable. People that do well here can self-manage but aren’t afraid to reach out for guidance and thrive in a creative problem-solving environment. We are proud to be recognized as one of the top workplaces in the tech industry.
MachineMetrics was named by Forbes as one of the top IoT companies to watch in 2019 and voted one of Built In’s 2020 Best Places to Work in Boston!
About The Role:
Data Science’s mission at MachineMetrics is to provide advanced analytics to the organization, employing predictive modeling skillsets not otherwise found in the company, manifesting ultimately in a predictive machining product. The predictive machining product allows MachineMetrics to deploy algorithms to edge devices and actuate commands remotely to machines - all the way from creating an alarm to stopping the machine. We employ methods such as physics modeling, machine learning, and big data analysis with cross-company data to achieve our goals. We work heavily with Engineering to productize our work - with Data Science focusing largely on the creation of effective algorithms, which are then handed over to the Edge team for deployment.
The Data Scientist - Research will work closely with engineering and data science to create, analyze, and help deploy complex algorithms related to predicting various phenomena on machines. They should be skilled in signal processing methods and have a strong familiarity with electrical/mechanical engineering principles, as our work revolves around state-of-the-art machine tools. They should be able to work independently and with minimal supervision, and ideally have experience piloting a medium-to-large scale independent research project themselves.
What You’ll Do:
- Pioneer research in manufacturing analytics
- Work with the data science team to identify and model various physical phenomena of machine-tools, including how cutting forces are affected by tool wear, material, and program geometry, as well as the thermo-electro-mechanical properties of drive motors and transmission systems. Be a subject matter expert in machining physics
- We consider each member of the data science team to be a subject matter expert (SME) in a particular area. This position would serve as the SME for machining physics/engineering, allowing us to learn about new modeling techniques specific to key components inside machine-tools (for example, feedback-controlled induction motors).
- Be an effective communicator and representative of the Data Science Team, both internally and externally
- We publish our work occasionally in peer-reviewed journals, such as Prognostics and Health Management, and write blogs in more informal venues as well. This member would be expected to contribute writing and thought leadership to these pieces and thus must be able to write clearly and concisely.
What You’ll Have:
- MS, M.Eng. or PhD in the physical sciences, computer science, electrical engineering, mechanical engineering, or other similar quantitative field
- 3-5+ years of relevant experience in a research oriented environment
- Familiarity with signal processing and machine learning methodologies; able to articulate key concepts and at least implement in pseudocode
- Prior experience with owning medium-to-large scale research or data science projects and presenting results to key stakeholders; able to logically support modeling approaches and cite benefits and drawbacks of alternatives to the business
- Prior experience with auditing models and performing quality control checks on other team members’ code and methods
- Prior experience with time-series data (bonus for experience in Spark and TimescaleDB)
- Effectively write SQL with an emphasis on efficiency of execution time
- Experience with R or Python, preferably with productionalized code
- Demonstrated ability to maintain performance level in a fast-paced environment with changing priorities and deadlines
- All qualified candidates must be legally authorized to work in the United States, as we deal with ITAR-related data (US Citizen or Permanent Resident only)
- You'll need a valid driver’s license, passport, ability to travel without restriction and reliable transportation
We are proud to be an equal opportunity employer who values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status
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