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Industrial Engineering Data Analyst Jobs (NOW HIRING)

Apex Systems

Data Analyst

Warren, MI · Hybrid

Job#: 3029487 Data Analyst - Manufacturing & Applied Machine Learning Location: Warren, MI (Hybrid ... A Master's or PhD in Mechanical Engineering, Industrial Engineering, or a related manufacturing ...

CYNET SYSTEMS

Industrial Engineer I

Whitakers, NC · On-site

$32/hr

The Industrial Engineer I will support manufacturing operations through process analysis ... Strong CAD review and engineering drawing interpretation skills. * Advanced Excel and data analysis ...

Cruz Associates Inc

Industrial Engineer

Indian Head, MD · On-site

$75K - $101K/yr

... industrial engineering or related field * Vast knowledge in Microsoft Office products (Word, Excel, and PowerPoint) * Ability to gain/maintain Secret Clearance * Strong analytic skills in data ...

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Industrial Engineering Data Analyst information

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$52.5K

$98.6K

$132.5K

How much do industrial engineering data analyst jobs pay per year?

As of Jun 14, 2026, the average yearly pay for industrial engineering data analyst in the United States is $98,591.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Industrial Engineering Data Analysts when working with manufacturing data?

Industrial Engineering Data Analysts often encounter challenges such as dealing with incomplete or inconsistent data from various manufacturing systems, integrating data from legacy equipment, and ensuring data accuracy for meaningful analysis. Additionally, translating complex analytical findings into actionable recommendations for engineers and production teams can require strong communication skills. Collaboration with cross-functional teams is essential to validate data assumptions and implement process improvements effectively.

Do industrial engineers do data analysis?

Yes, industrial engineers often perform data analysis to improve processes, optimize systems, and increase efficiency. They use tools like statistical software and data visualization to interpret operational data and support decision-making.

Is ISE a good degree?

Industrial Engineering Data Analysts typically hold a degree in industrial engineering or a related field, which provides skills in process optimization, data analysis, and systems improvement. The degree is considered valuable for roles that require analytical thinking, problem-solving, and proficiency with tools like Excel, SQL, and statistical software. It can lead to diverse career opportunities in manufacturing, logistics, healthcare, and consulting industries.

Is data analyst still relevant in 2026?

Data analysts, including those in industrial engineering, remain relevant in 2026 as organizations continue to rely on data-driven decision making. Skills in data visualization, statistical analysis, and tools like SQL and Excel are essential, and the role is expected to evolve with advancements in automation and machine learning. Continuous learning and adapting to new technologies will help data analysts stay valuable in the job market.

What is the difference between Industrial Engineering Data Analyst vs Industrial Engineer?

AspectIndustrial Engineering Data AnalystIndustrial Engineer
Required CredentialsBachelor's in Industrial Engineering, Data Analysis, or related field; proficiency in data toolsBachelor's in Industrial Engineering or related field; engineering licensure optional
Work EnvironmentOffice settings, data centers, manufacturing plantsManufacturing facilities, offices, production environments
Employer & Industry UsageManufacturing, logistics, consulting firmsManufacturing, supply chain, process improvement
Common Search & ComparisonYesYes

While both roles focus on improving industrial processes, the Industrial Engineering Data Analyst primarily analyzes data to identify efficiencies, whereas the Industrial Engineer designs and implements systems for process improvement. The roles often overlap but differ in focus: data analysis versus engineering design.

Is 40 too late for data science?

For an industrial engineering data analyst, starting a career in data science at age 40 is feasible, as the field values skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant tools like Python, R, and SQL, and gaining certifications or training. Age is less important than your ability to develop technical skills and adapt to evolving technologies.

What are the key skills and qualifications needed to thrive as an Industrial Engineering Data Analyst, and why are they important?

To thrive as an Industrial Engineering Data Analyst, you need strong analytical abilities, a background in industrial engineering or a related field, and proficiency in data analysis and statistical methods. Familiarity with tools such as SQL, Python or R, and data visualization platforms like Tableau or Power BI, along with knowledge of manufacturing systems, are typically required. Excellent problem-solving, communication, and teamwork skills are vital for effectively translating data insights into operational improvements. These skills and qualities are crucial to optimize processes, reduce costs, and support data-driven decision-making in industrial environments.

What does an Industrial Engineering Data Analyst do?

An Industrial Engineering Data Analyst collects, analyzes, and interprets data to help organizations optimize their operations, improve efficiency, and reduce costs. They use statistical methods, data visualization, and process modeling to identify trends and recommend improvements in manufacturing, logistics, or supply chain processes. Their work often involves collaborating with engineers, managers, and IT staff to implement data-driven solutions that enhance productivity and quality.
What cities are hiring for Industrial Engineering Data Analyst jobs? Cities with the most Industrial Engineering Data Analyst job openings:
Infographic showing various Industrial Engineering Data Analyst job openings in the United States as of June 2026, with employment types broken down into 2% Locum Tenens, 6% As Needed, 65% Full Time, 7% Part Time, and 20% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $98,591 per year, or $47.4 per hour.

Industrial Engineer -IB4

Foxconn Industrial Internet - FII

Houston, TX • On-site

$66K - $90K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 16 days ago

Job description

Key Responsibilities
Manufacturing Process Optimization
  • Lead analysis and improvement of manufacturing processes to maximize efficiency, throughput, and quality.
  • Develop and maintain time studies, line balancing, capacity models, and labor standards.
  • Optimize factory layout, material flow, workstation design, and ergonomics.
  • Support automation and digital manufacturing initiatives (MES, data analytics, Industry 4.0).
Cost, Productivity & Capacity
  • Drive labor productivity improvements and cost-reduction initiatives.
  • Support annual operating plans through capacity planning and headcount modeling.
  • Identify bottlenecks and implement sustainable solutions to improve OEE and cycle time.
New Product Introduction (NPI)
  • Partner with Product Engineering and Operations during NPI to ensure manufacturability and scalability.
  • Support DFM/DFA reviews and production ramp readiness.
  • Define standard work and process documentation for new lines and products.
Data Analysis & Continuous Improvement
  • Analyze manufacturing data to identify trends, risks, and improvement opportunities.
  • Lead Lean, Six Sigma, and Kaizen initiatives across production and support functions.
  • Establish KPIs and dashboards to monitor performance and drive accountability.

Cross-Functional Collaboration
  • Collaborate with Manufacturing, Quality, Supply Chain, Facilities, and Program Management teams.
  • Support root cause analysis and corrective actions for production issues.
  • Mentor junior engineers and technicians on industrial engineering best practices.

Required Qualifications
  • Bachelor’s degree in Industrial Engineering, Manufacturing Engineering, Mechanical Engineering, or related field.
  • 2+ years of experience in industrial engineering within electronics or high-tech manufacturing.
  • Strong knowledge of Lean Manufacturing, Six Sigma, and continuous improvement methodologies.
  • Experience with high-mix/high-volume electronics manufacturing (SMT, PCBA, systems integration preferred).
  • Proficiency in time studies, capacity planning, line balancing, and labor modeling.
  • Strong data analysis skills (Excel, Minitab, Power BI, or similar tools).

Preferred Qualifications
  • Master’s degree in Industrial Engineering or MBA.
  • Lean Six Sigma Black Belt or Green Belt certification.
  • Experience supporting automation, robotics, or smart factory initiatives.
  • Familiarity with MES, ERP, and manufacturing analytics systems.
  • Experience in regulated or quality-critical environments (ISO, IPC, etc.).

Key Competencies
  • Strong analytical and problem-solving skills
  • Hands-on, data-driven mindset
  • Ability to influence cross-functional teams
  • Excellent communication and presentation skills
  • Comfortable working in fast-paced, changing environments
​
Benefits:
  • Medical, dental, and vision insurance 
  • Company-paid life insurance and short-term disability
  • HSA and FSA options with tax advantages
  • Employee Assistance Program (EAP) and wellness resources
  • Voluntary benefits including life, AD&D, and long-term disability
  • 401 (k) plan with company match
  • Fitness and wellness programs

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