MID LEVEL DATA ANALYST

Key Responsibilities / KRAs:

• Data Collection and Management
• Collect, clean, and validate data from production lines, ERP systems, CRM, and other internal databases.
• Maintain accurate and up-to-date datasets for production, inventory, sales, and quality metrics.
• Ensure compliance with data privacy and governance policies.
• Data Analysis and Reporting
• Analyze production efficiency, scrap rates, downtime, and defect trends.
• Generate daily, weekly, and monthly reports on production, inventory, sales, and quality KPIs.
• Identify patterns, anomalies, and trends to support operational improvements.
• Process Optimization & Insights
• Collaborate with production, quality, and supply chain teams to optimize manufacturing processes.
• Conduct root cause analysis for production inefficiencies and quality issues.
• Recommend actionable solutions based on data-driven insights.
• Dashboard Development & Visualization
• Develop and maintain dashboards using Power BI, Tableau, or Excel to present KPIs.
• Provide visualizations to enable managers to make informed decisions quickly.
• Forecasting & Trend Analysis
• Support demand forecasting, inventory planning, and capacity utilization analysis.
• Predict potential production bottlenecks using historical data trends.
• Cross-Functional Collaboration
• Work closely with operations, procurement, quality, and sales teams to understand data needs.
• Provide analytical support for strategic projects such as cost reduction, capacity expansion, and new product launches.

Key Performance Indicators (KPIs):

KRA

KPI

Target / Metric

Data Accuracy & Integrity

Data error rate in reports

< 2%

Reporting & Analysis

Timeliness of reports (daily/weekly/monthly)

100% on-time delivery

Production Insights

Number of actionable insights generated

≥ 5 per quarter

Process Improvement Support

Reduction in scrap or downtime based on analysis

≥ 5% improvement YoY

Dashboard Management

Dashboard uptime and update frequency

100% uptime, updated weekly

Forecasting Accuracy

Accuracy of production/sales forecasts

≥ 85% accuracy

Cross-Functional Support

Stakeholder satisfaction score

≥ 8/10

Training & Knowledge Sharing

Number of knowledge-sharing sessions conducted

≥ 2 per quarter

Qualifications & Skills:

• Bachelor’s degree in Statistics, Data Science, Industrial Engineering, or related field.
• 3–5 years of experience in data analysis, preferably in manufacturing or operations.
• Proficiency in Excel, SQL, Python/R, and data visualization tools like Power BI/Tableau.
• Strong analytical and problem-solving skills.
• Knowledge of manufacturing processes, supply chain, and quality metrics preferred.
• Excellent communication skills to translate data into actionable business insights.

Personal Attributes:

• Detail-oriented and highly organized.
• Curious mindset with a continuous improvement attitude.
• Ability to work collaboratively across teams and handle multiple priorities.