Deskripsi Pekerjaan Discovery & Diagnosis: Identify operational gaps, KPI declines, and improvement opportunities across departments through rigorous data exploration, ensuring findings are grounded in accurate, verifiable evidence and presented with honesty and transparency. Data Collection & Baseline: Collect and validate data from system logs, direct process observations, and performance reports to establish a reliable baseline that reflects actual operational conditions, upholding Honesty by ensuring data integrity and accurate representation of performance realities. Advanced Analytics: Analyze operational and performance trends using tools such as R, Python, or SQL to generate statistically sound and defensible conclusions, demonstrating Agility in adapting analytical approaches to evolving business questions and datasets. Insight Generation: Translate complex analytical outputs into structured, strategic reports, delivering clear and objective recommendations to stakeholders with Empathy by tailoring communication to their context, priorities, and level of technical understanding. Impact Validation: Assess post-implementation results using measurable indicators to quantify real-world outcomes and calculate Return on Investment (ROI), reflecting Honesty through objective evaluation of both successes and limitations. Monitoring & Dashboarding: Develop and maintain performance dashboards that provide transparent visibility into key metrics, reinforcing Agility by enabling timely response to performance shifts and emerging risks. Triad Collaboration: Partner closely with the Process Improvement Specialist to supply reliable data insights that support evidence-based decision-making, practicing Empathy through constructive collaboration and shared accountability for outcomes. Kualifikasi Education: Bachelor’s degree in Industrial Engineering or Information Systems. Experience: 2+ years of experience as an operations analyst, performance analyst, or in a data-driven project improvement role. Methodology: Strong knowledge of Lean Six Sigma Green Belt (LSSGB) principles to understand the project lifecycle. Technical

• Proficient in data analysis tools and languages such as R, Python, SQL, an Excel.

• Communication: Excellent stakeholder management skills with the ability to translate technical data into business language.

• Analytical Mindset: High attention to detail and accuracy when validating data to ensure the integrity of "Impact Assessment" reports.