Deskripsi Pekerjaan
Central Proteina Prima is seeking a detail-oriented Data Analyst to drive data-driven decision making in our dynamic animal feed industry. You will be pivotal in transforming raw data into actionable insights that optimize product formulations, enhance performance metrics, and advance our Feed Technology initiatives. This role requires a blend of technical expertise and business acumen to uncover trends, identify opportunities, and support strategic growth across operations.
As a key member of our analytics team, you'll collaborate with cross-functional departments to translate complex datasets into clear, compelling narratives that inform product development, operational efficiency, and market strategies. Your work will directly contribute to maintaining our competitive edge in the animal nutrition sector while ensuring data integrity and analytical rigor throughout the organization.
Tanggung Jawab
- Collect, process, and analyze data related to product formulations, product performance metrics, and Feed Technology activities
- Develop and maintain automated reporting systems to track key performance indicators
- Collaborate with R&D and production teams to analyze test results and optimize product formulations
- Create comprehensive data visualizations and dashboards for stakeholder reporting
- Conduct statistical analysis to identify trends, anomalies, and improvement opportunities
- Support implementation of data-driven quality control processes
- Document methodologies and maintain data governance standards
Kualifikasi
- S1 degree in Statistics, Mathematics, Computer Science, Engineering, or related quantitative field
- Minimum 2 years of experience in data analysis or business intelligence
- Proficiency in SQL, Excel, and statistical analysis tools (R/Python preferred)
- Strong understanding of data visualization principles and tools (Tableau/Power BI)
- Experience with product performance analysis or manufacturing data
- Excellent problem-solving skills with attention to detail
- Ability to translate complex findings for non-technical stakeholders