Where mechanical engineering meets data - turning engineering and supply chain data into actionable insights..
class SaitejMatta:
def __init__(self):
self.role = ["Data Analyst", "Supply Chain Analyst", "Mechanical Engineer"]
self.background = "Mechanical Engineering (Minor: Supply Chain Management)"
self.focus = "Reliability & Supply Chain Analytics"
self.current_project = "Retail Supply Chain Analytics Project"
I bring an engineer's lens to data - diagnosing systems, tracing root causes, and modeling degradation and risk rather than just reporting numbers. My work sits at the overlap of rotating equipment reliability and supply chain performance analytics.
|
End-to-end analysis of a 180K+ order retail supply chain dataset - covering data cleaning, sales/revenue/profit EDA, discount and customer segmentation analysis, and logistics/geographic performance. Surfaces insights on late delivery risk, margin erosion from discounting, and regional fulfillment bottlenecks. |
|
Condition monitoring and Remaining Useful Life (RUL) trend analysis for mechanical seals - combining mechanical engineering domain knowledge with degradation-pattern analytics to anticipate failure before it happens. |
| Data Analytics |
BI & Visualization
Domain Knowledge |
Engineering & CAD/Simulation |