Position: In House M- F
Hours: 7:30 - 4:30
Salary: 65,000 - $85,000
The nature of this role
This is a floor role that produces data, not an office role that produces reports.
The department's constraint is not a shortage of dashboards — it is that the process does not yet generate information anyone can rely on. The deliverable of this position is working measurement: capture designed at the point and moment the work happens, accurate enough to make decisions on, and durable enough to keep running without the post-holder standing over it. Analysis follows measurement; it does not substitute for it.
Position Summary
The Manufacturing Systems & Data Analyst gives the Assembly department numbers it can trust. The role designs and installs practical measurement on the shop floor, owns the accuracy of what is captured, and converts it into the small set of measures the department uses to run itself and to make decisions.
Hours are recorded against jobs and the detail exists in the system, but it is reported in aggregate: the capability to extract it, break it down, reconcile it and establish whether it is accurate does not exist in the department's structure today. Figures therefore cannot be traced to a cause or defended when they conflict with what is visible on the floor. Staffing is planned by section count rather than by the work a job actually contains.
Wherever the department needs to see something it currently cannot — where time is going, what capacity is genuinely available, what a job costs against what was quoted, whether a change actually improved anything — or needs to confirm that something it already reports is true, this role builds the means to do it, proves the figure is sound, and keeps it sound once built.
Essential Duties and Responsibilities
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Design and install shop-floor data capture that people will actually complete — developed with the teams doing the work rather than issued to them — and own its accuracy. Capture that takes more than a minute does not get done, and partial data is more dangerous than none because it appears complete.
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Own data integrity as a deliverable, including capture rate: reconcile what is recorded against what actually occurred, and do not publish analysis built on data whose completeness is unknown.