Data Analyst

Torch.id
Kota Bandung
IDR 200,000,000 - 300,000,000
Job description

Job Overview:

We are currently seeking a driven Data Analyst to join our team. The selected candidate will possess the ability to translate raw data into valuable insights, enabling informed business decisions. Working across diverse departments, including stock and inventory, as well as sales and marketing, this role plays a pivotal role in enhancing our data-driven operations.

Job Roles:

  1. Interpret and analyze data using advanced statistical methods.
  2. Design and implement effective data analysis strategies and collection systems for optimal statistical accuracy and quality.
  3. Execute data cleansing and Extract, Transform, Load (ETL) processes.
  4. Develop data visualizations using advanced Power BI capabilities.
  5. Collaborate with management to prioritize information needs and align with business objectives.
  6. Identify and define opportunities for process enhancements and optimization.

Qualifications:

  1. Profound expertise in mathematical, statistical, and analytical thinking (essential).
  2. Proficiency in spreadsheet applications, including intermediate-level Microsoft Excel and Google Sheets skills (essential).
  3. Strong command of data visualization tools, including Power BI (DAX, Power Query) and Looker Data Studio.
  4. Familiarity with SQL Server databases.
  5. Proficient in programming language, particularly Python.
  6. Exceptional problem-solving skills.
  7. Meticulous attention to detail and accuracy.
  8. Skilled in query formulation, report generation, and presentation creation.
  9. Effective team collaborator and team player.
  10. Excellent verbal and written communication skills, with a strong command of English being advantageous.
  11. Exceptional communication and presentation abilities.
  12. Entry-level candidates are welcome; however, proven experience in data analysis is advantageous.
  13. Prior experience in retail or fashion sectors is a plus.
  14. Bonus points for involvement in Machine Learning projects such as Recommender Systems, RFM Segmentation, and Time-Series Forecasting.
  15. A commitment to continuous learning is mandatory.
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