About us

Kilap Global consists of several brands, which are Kilap Premium, Dakter, Otoke, and KilapLab. Kilap Premium is the main specialist in motorcycle care especially in washing category, helmet are and doff care. This brand was established in late 2017 by the Founder Dzahaby Razan in Greater Malang, East Java. Until this day Kilap Premium has sold more than 300 thousand, distributed in 80 distributors and resellers located in all over Indonesia. Kilap Premium is estimated to have more than 50.000 customers. In the end of 2022, Kilap Global Group was established to develop other brands and different variety of cunsomer segments therefore wider the market in household category to B2B chemical solution. Till date, the new brand has more than 1000 user and 5 organizational clients.

Qualifications & experience

• Proficiency in programming languages such as SQL, Python, R, or other statistical analysis tools.
• Strong analytical and problem-solving skills.
• Knowledge of data visualization tools like Tableau, Power BI, or matplotlib.
• Familiarity with statistical methods and machine learning algorithms.
• Excellent communication and presentation skills.
• Understanding of database management systems and data warehousing concepts.
• Time management and ability to prioritize tasks effectively.

Tasks & responsibilities

• Data Collection: Gather data from various sources such as databases, spreadsheets, APIs, and external sources.
• Data Cleaning and Preprocessing: Clean, transform, and preprocess data to ensure accuracy, completeness, and consistency.
• Data Analysis: Apply statistical methods, data mining techniques, and machine learning algorithms to analyze datasets and extract meaningful insights.
• Data Visualization: Create clear and informative visualizations (charts, graphs, dashboards) to communicate findings and trends to stakeholders.
• Reporting: Prepare and present reports summarizing key findings, trends, and recommendations derived from data analysis.
• Statistical Analysis: Perform statistical tests and analysis to validate hypotheses, identify correlations, and uncover patterns in data.
• Predictive Modeling: Develop predictive models to forecast future trends, behavior, or outcomes based on historical data.
• Database Management: Maintain and manage databases, ensuring data integrity, security, and accessibility.
• Collaboration: Work closely with cross-functional teams such as business analysts, engineers, and decision-makers to understand data requirements and provide analytical support.
• Continuous Improvement: Stay updated on industry trends, tools, and techniques in data analysis and contribute to the enhancement of data analytics processes within the organization.