Industrial Operations Analyst

Placements24; Cape Town; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Bonuses

Medical aid

Retirement fund

Training programs

Hybrid role

Wellness programs

Annual leave

Job summary

Placements24 in Cape Town seeks a proactive Industrial Operations Analyst to join our client’s team. You will collect and analyze production data, build dashboards, and provide data-driven recommendations to boost efficiency, reduce costs, and improve quality.

Candidates should have 3+ years in industrial analytics, strong Excel and SQL skills, and experience with Tableau or Power BI. This hybrid Cape Town role offers collaboration with engineering and production and opportunities for

Qualifications

• 3+ years of experience in an analytical role within industrial/manufacturing settings.
• Proficiency in Excel (pivot, advanced functions), SQL, and at least one statistical tool (R or Python).
• Experience with data visualization tools to create dashboards and reports.

Responsibilities

• Collect, organize, and analyze large production datasets (output, material flow, equipment, labor).
• Develop and maintain dashboards to track KPIs for industrial operations.
• Identify trends and anomalies to pinpoint inefficiencies or risks.
• Conduct root cause analysis for production deviations.
• Formulate data-driven recommendations for process improvements and cost savings.
• Collaborate across engineering, production, and supply chain to implement solutions.
• Develop process documentation and SOPs from analytical findings.
• Present findings clearly to management and operational teams.
• Assist in implementing and monitoring process changes and efficiency initiatives.
• Stay updated on best practices in industrial analytics.

Skills

Excel advanced

SQL

R

Python

Tableau

Power BI

Manufacturing processes

Lean Six Sigma

Data visualization

Communication

Education

Bachelor's in Industrial Engineering

Tools

Tableau

Power BI

Excel

SQL

Job description

About the Role

Our client is seeking a proactive and data-driven Industrial Operations Analyst to join their established team in Cape Town. This hybrid role offers a fantastic opportunity to contribute to the continuous improvement of complex industrial processes within a leading organization. You will be instrumental in gathering, analyzing, and interpreting operational data to identify trends, inefficiencies, and areas for enhancement. The successful candidate will work closely with production managers, engineers, and other stakeholders to develop data-backed recommendations that drive efficiency, cost reduction, and quality improvements. This position requires a blend of strong analytical acumen, an understanding of industrial processes, and excellent communication skills to effectively present findings and advocate for change. You will have the chance to make a tangible impact on our client's operational success through insightful analysis and strategic recommendations. This role is perfect for someone who enjoys dissecting complex systems and uncovering opportunities for optimization.

Key Responsibilities

• Collect, organize, and analyze large datasets related to production output, material flow, equipment performance, and labor efficiency.
• Develop and maintain dashboards and reports to track key performance indicators (KPIs) for industrial operations.
• Identify trends, patterns, and anomalies within operational data to pinpoint areas of inefficiency or potential risk.
• Conduct root cause analysis for production deviations and operational issues.
• Formulate data-driven recommendations for process improvements, cost savings, and enhanced productivity.
• Collaborate with cross-functional teams, including engineering, production, and supply chain, to gather information and implement solutions.
• Develop and refine process documentation and standard operating procedures based on analytical findings.
• Present findings and recommendations clearly and concisely to management and operational teams.
• Assist in the implementation and monitoring of process changes and efficiency initiatives.
• Stay abreast of industry best practices and emerging technologies in industrial analytics and operations management.

Requirements

• Bachelor's degree in Industrial Engineering, Operations Research, Statistics, Business Analytics, or a related quantitative field.
• Minimum of 3 years of experience in an analytical role, preferably within an industrial or manufacturing setting.
• Proven proficiency in data analysis tools and techniques, such as Excel (advanced functions, pivot tables), SQL, and statistical software (e.g., R, Python for data analysis).
• Experience with data visualization tools (e.g., Tableau, Power BI) to create insightful reports and dashboards.
• Strong understanding of manufacturing processes, supply chain principles, and operational metrics.
• Excellent analytical and problem-solving skills with meticulous attention to detail.
• Effective written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences.
• Ability to work effectively both independently and as part of a hybrid team.
• Strong organizational and time management skills.
• Experience with Lean Manufacturing or Six Sigma methodologies is a plus.

Benefits

• Our client offers a competitive remuneration package including a good base salary and performance-related bonuses.
• Employees benefit from comprehensive medical aid and retirement fund contributions.
• There are opportunities for professional development through internal training programs and support for external certifications.
• This hybrid role allows for a balance between in-office collaboration in Cape Town and remote flexibility, with dedicated workspace facilities provided.
• You will be part of a supportive and innovative work environment where your analytical contributions are highly valued.
• We offer a generous annual leave allowance and access to wellness programs.
• Join a team committed to driving operational excellence through data-driven insights.