āļāļĢāļ°āļāļēāļĻāļāļēāļāļāļĩāđāļŦāļĄāļāļāļēāļĒāļļāđāļĨāđāļ§
Data Analytics / āļāļąāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļāļĄāļđāļĨ
āļāļĩāđāļāļĢāļīāļĐāļąāļ āļāļĩāļāļĩāļāļĩ āđāļāđāļāđāļāļāļĒāļĩ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ)Data Analyst and BI â PTGâs Business
At PTG Energy Group, data drives all of our decision-making. As part of the Business Intelligence team, data will be used for informing business decisions across the company. Likewise, technical skills, business acumen and creativity built tools to quickly automate reporting and generate information insight that how our key business are performing.
As a Business Intelligence (BI) and Data Analyst, you will be able to support PTGâs business in analyzing, combine business acumen, technology and innovation to organize data, enable insights and create a data-driven as much as you can.
Responsibilities :
- Be the partner with PTGâs business teams, understand their data needs, and build plans to address those with intelligent data on time.
- To tell a story and provide insights to the users enabled to make better decision by delivering data solution.
- Use statistical tools to identify, analyze, and interpret patterns, trends and insights in complex data sets that could be helpful for the diagnosis and prediction to support PTGâs business.
- Responsible for planning and providing final analysis report for PTGâs business to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
- Encourage and collaborate with multiple internal stakeholders to use statistical / analytical tools in planning and decision-making process.
Minimum qualifications :
- Bachelorâs degree in computer science, data analytics, statistics, economics or related fields.
- Proficient in data analytics tools and other computer programs; MS Word, Excel, PowerPoint etc.
- Excellent communication skill both in Thai and English.
- Experience in programming and SQL.
- Able to work under pressure and with multiple stakeholders within limited timeline.
- Interested in new technologies / innovations.
Preferred qualifications :
- Master's degree in a quantitative discipline.
- At least 1-2 years of experience in a similar role preferably with solid knowledge in food & beverage industry , CRM and retail business.
- Experience working on teams that managed large scale data projects.
- Knowledge with Data Science, Advanced Analytics, Machine learning tools, and methodologies.
- Conceptual, logical and physical data modeling, and data architecture knowledge.
- Visualization expertise in tools like Tableau and Power BI etc.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļĩāđāļāļģāđāļāđāļ
- āđāļĄāđāļĢāļ°āļāļļāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļąāđāļāļāđāļģ
āđāļāļīāļāđāļāļ·āļāļ
- āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
āļŠāļēāļĒāļāļēāļ
- āļāļąāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđ
- āđāļāļāļĩ / āđāļāļĩāļĒāļāđāļāļĢāđāļāļĢāļĄ
- āļāļēāļāļ§āļīāļāļąāļĒāđāļĨāļ°āļ§āļīāļāļĒāļēāļĻāļēāļŠāļāļĢāđ
āļāļĢāļ°āđāļ āļāļāļēāļ
- āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļīāļĐāļąāļ
āđāļĄāļ·āđāļ 20 āļāļ§āđāļēāļāļĩāļāđāļāļ āđāļāļ§āļąāļāļāļĩāđ 21 āļĄāļĩāļāļēāļāļĄ 2531 āļāļĢāļīāļĐāļąāļ āļ āļēāļāđāļāđāđāļāļ·āđāļāđāļāļĨāļīāļ āļāļģāļāļąāļ āđāļāđāļāđāļāļāļąāđāļāļāļķāđāļāļāļāļāļ§āļēāļĄāļāļąāđāļāđāļ āļāļĢāļ°āļāļāļāļāļīāļāļāļēāļĢāļāļĨāļąāļāļāđāļģāļĄāļąāļ āđāļĨāļ°āļāđāļēāļāđāļģāļĄāļąāļāđāļāļ·āđāļāđāļāļĨāļīāļāđāļŦāđāļāļąāļāļāļļāļĄāļāļ āļāļđāđāļāļĢāļ°āļāļāļāļāļēāļĢāļāļĢāļ°āļĄāļāđāļĨāļ°āđāļĢāļāļāļēāļāļāļļāļāļŠāļēāļŦāļāļĢāļĢāļĄ āđāļĢāļīāđāļĄāļāđāļāļāļēāļāļ āļēāļāđāļāđāļāļāļāļāļĢāļ°āđāļāļĻāđāļāļĒ āļāļēāļāļāļĢāļīāļĐāļąāļ āļ āļēāļāđāļāđāđāļāļ·āđāļāđāļāļĨāļīāļ āļāļģāļāļąāļ āđāļāđāļāļāļāļ°āđāļāļĩāļĒāļāđāļāļĨāļĩāđāļĒāļāļŠāļđāđ āļāļĢāļīāļĐāļąāļ āļ ...
āļĢāđāļ§āļĄāļāļēāļāļāļąāļāđāļĢāļē: Joining PTG means becoming part of a dynamic and innovative company that is committed to sustainable growth and customer satisfaction. With over 30 years of experience, PTG offers a collaborative work environment that encourages personal and professional development.
āļŠāļ§āļąāļŠāļāļīāļāļēāļĢ
- āļāļēāļĢāļāļąāļāļāļēāđāļāļ·āđāļāļāļ§āļēāļĄāđāļāđāļāļĄāļ·āļāļāļēāļāļĩāļ
- āļāđāļēāđāļāļīāļāļāļēāļ
- āļāļģāļāļēāļāļāļāļāļŠāļāļēāļāļāļĩāđ
- āļāļĢāļ°āļāļąāļāļāļĩāļ§āļīāļ
- āļāļĢāļ°āļāļąāļāļŠāļąāļāļāļĄ
- āļāļĢāļ°āļāļąāļāļŠāļļāļāļ āļēāļ
- āļāļķāļāļāļāļĢāļĄ
- āđāļāļāļąāļŠāļāļķāđāļāļāļĒāļđāđāļāļąāļāļāļĨāļāļēāļ
- āļāļĢāļ°āļāļąāļāļāļļāļāļąāļāļīāđāļŦāļāļļ
- āđāļāļāļąāļŠāļāļķāđāļāļāļĒāļđāđāļāļąāļāļāļĨāļāļĢāļ°āļāļāļāļāļēāļĢ
- āđāļāļĢāļ·āđāļāļāđāļāļāļāļāļąāļāļāļēāļ
- āđāļāļĢāļāļāļēāļĢāļŠāđāļāđāļŠāļĢāļīāļĄāļāļļāļāļ āļēāļāļāļĩāļ§āļīāļ
- āļŠāđāļ§āļāļĨāļāļāļāļąāļāļāļēāļ
- āļŠāļĄāļēāļāļīāļāļāļīāļāđāļāļŠ
- āđāļāļāļēāļŠāđāļāļāļēāļĢāđāļĢāļĩāļĒāļāļĢāļđāđāđāļĨāļ°āļāļąāļāļāļē
- āļāđāļēāļĒāļāđāļēāļāļģāļāļēāļāļĨāđāļ§āļāđāļ§āļĨāļē
- āļāļāļāļāļļāļāļŠāļģāļĢāļāļāđāļĨāļĩāđāļĒāļāļāļĩāļ