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Commercial Revenue & Analytics Assistant Manager

Ninja Van

Ninja Van

Data Science
Jakarta, Indonesia
Posted on Wednesday, July 3, 2024
Ninja Van is a tech-enabled logistics company on a mission to provide hassle-free delivery services for businesses of all sizes across Southeast Asia. Launched in 2014, we started operations in Singapore and have become the region's largest and fastest growing last-mile logistics company, partnering with over 35,000 merchants and delivering more than 1,000 parcels every minute across six countries.
At our core, we are a technology company that is disrupting a massive industry with cutting-edge software and operational concepts. Powered by algorithm-based optimisation, dynamic routing, end-to-end tracking and a data-driven approach, we provide best-of-class delivery services that delight both the shippers and end customers. But we are just getting started! We have much room for improvement and many ideas that will further shape the industry.

Responsibilities

  • Assisting in analysing monthly revenue from invoice
  • Gather data to calculate company revenue per sales channel
  • Create script to transform monthly invoice data in shape that can be analysed
  • Processing and analysing volume distribution as a supporting data
  • Coordinate with stakeholders to set volume & revenue budget based on data
  • Developing presentation deck and report to management, and also delivering insights to management.
  • Create, execute & maintain commercial KPI and incentive scheme
  • Create commission scheme for mitra to increase attractiveness

Requirements

  • Education degree: Bachelor Degree in Economics and Business, Industrial Engineering, Information Technology, Statistics or Engineering. Preferably from reputable universities.
  • Working experience: preferably 2 years of experience as a data analyst or commercial revenue analyst
  • Advanced in using Microsoft Excel
  • Fluent with SQL, Python, R or other scripting/programming languages to problem-solve.
  • Experienced with working with very large datasets
  • Have high curiosity and eager to learn in a fast paced environment also self learn under minimal direction
  • Have strong communication, excellent problem solving, critical thinking, detail oriented and data driven
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