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Process Improvement Analyst

Job in Erlanger, Kenton County, Kentucky, 41018, USA
Listing for: Insight Global
Full Time position
Listed on 2026-07-09
Job specializations:
  • Business
    Data Analyst, Business Systems & Technology Analysis, Business Analyst, Business Intelligence
Salary/Wage Range or Industry Benchmark: 70000 - 90000 USD Yearly USD 70000.00 90000.00 YEAR
Job Description & How to Apply Below

Qualifications

  • 2-3+ years of Process Engineering / Industrial Engineering experience
  • Knowledge of process engineering, operations, or analytics-related roles
  • Strong analytical and problem-solving skills
  • Track record in process mapping and data analysis
  • Microsoft Excel (advanced formulas, pivot tables, data analysis)
  • Process mapping tools (e.g., Visio, Lucidchart, Miro)
  • Basic to intermediate SQL for data extraction and manipulation
  • Ability to work in a fast-paced, operational environment (warehouse, logistics, or manufacturing preferred)
  • Familiarity with Lean, Six Sigma, or continuous improvement methodologies
  • Experience with data tools such as Snowflake, Power BI, Tableau, Python, or similar analytics platforms
  • Experience conducting time studies or labor standards development
Day to Day:

Industrial Engineer – Process Optimization:
To support process improvement initiatives through process mapping, time studies, and data‑driven analysis. These roles will work closely with operations and engineering leadership to document current‑state processes, identify inefficiencies, and support actionable improvements.

Key Responsibilities:

Process Mapping & Documentation
  • Develop current-state and future-state process maps using standard methodologies (e.g., SIPOC, swimlane diagrams, value stream mapping)
  • Conduct on‑site observations to accurately document workflows, task sequences, and process variations
  • Identify process bottlenecks, redundancies, and opportunities for standardization
Time Studies & Work Measurement
  • Perform detailed time studies and work sampling across operational processes
  • Analyze cycle times, wait times, utilization, and variability
  • Establish labor standards and productivity benchmarks
  • Validate findings through repeat observations and data triangulation
Data Analysis & Insights
  • Collect, clean, and analyze operational data from multiple sources
  • Query and extract data from enterprise databases (e.g., SQL, Snowflake, or similar platforms)
  • Develop dashboards, reports, and visualizations to communicate findings
  • Translate data into actionable insights and recommendations
  • Support root cause analysis using statistical and analytical techniques
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