Deskripsi Pekerjaan
Are you a seasoned data professional ready to lead strategy and operational excellence? We are seeking an experienced Data Analyst (Head Level) to join our team in Denpasar Utara, Bali. In this pivotal role, you will bridge the gap between complex data sets and high-level decision-making. You will be responsible for overseeing logistics data streams, optimizing operational efficiency, and driving the analytical framework that supports our company's growth.
The ideal candidate is a strategic thinker who can translate raw information into actionable business insights. You will mentor junior staff, manage large-scale data projects, and serve as the primary subject matter expert for our logistical and operational data infrastructure. If you possess a blend of leadership prowess, technical proficiency, and a passion for data-driven optimization, we invite you to apply.
Tanggung Jawab
- Lead and oversee the entire data analytics lifecycle for logistics and operational departments.
- Define Key Performance Indicators (KPIs) to monitor operational health and departmental efficiency.
- Develop and maintain high-level dashboards for senior management to track performance trends.
- Conduct deep-dive statistical analysis to identify bottlenecks in supply chain and logistics processes.
- Mentor and guide team members, fostering a culture of data-driven decision-making.
- Collaborate with cross-functional stakeholders to align data initiatives with business objectives.
- Automate reporting workflows to ensure accuracy and timely delivery of operational insights.
Kualifikasi
- Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, or a related field.
- Minimum 5+ years of experience in data analytics, with at least 2 years in a leadership or managerial capacity.
- Expertise in SQL, Python or R, and proficiency with BI tools like Tableau, Power BI, or Looker.
- Strong background in logistics, supply chain analytics, or operational management.
- Excellent communication skills with the ability to translate technical findings for non-technical stakeholders.
- Demonstrated experience in managing data architecture and ensuring data integrity.
- Strong problem-solving mindset with a focus on process improvement and scalability.