Team Introduction

The Pricing team at DiDi Labs tackles challenging engineering and data science problems in the wide spectrum of pricing, fares and incentives, supporting DiDi’s fast-growing international business (i.e., the world outside China). The mission is to improve key business metrics, enhance marketplace efficiency, elevate the experiences of our global customers, and build various pricing-related products that will continue to change the global transportation landscape.

The team is composed of machine learning engineers, backend engineers and data scientists. We use machine learning, operations research, statistics, economics and other quantitative techniques to design efficient pricing algorithms and strategies. We also build big data pipelines and scalable backend systems to deliver strategies and products in the real business.

Responsibilities

  • Build models and design algorithms in the wide pricing domain, using machine learning, operations research, statistics, economics, and/or other quantitative techniques. The work needs to be end-to-end, starting from idea brainstorming and data exploration, and ending with implementing the code in production.
  • Develop simulators to evaluate the performance of pricing strategies offline, and design experiments to evaluate the strategies online.
  • Perform data analysis for pricing strategy development and post-experiment evaluation.
  • Closely collaborate with engineers in the pricing team here, product managers and data analysts in China HQ, and local operation teams in international cities (e.g. Latin America). 
  • The goal is to improve key business metrics in our international business and make direct business impacts. 

Qualifications

  • M.S. degree (Ph.D. is a plus) in Computer Science, Operations Research, Statistics, Engineering, Economics, Math, or a similar quantitative field.
  • 2+ years of industry experience in machine learning and/or operations research. Strong fresh PhD with research focus on the related fields will also be considered.
  • Domain knowledge in pricing and revenue management.
  • Hands-on mastery of data manipulation and experience with data analytics tools (SQL, Python, Hadoop, Hive, Spark, etc.).
  • Solid programming skills. Familiar with basic data structures and algorithms.
  • Strong verbal and written communication skills.
  • Be able to display leadership qualities and enthusiasm to engage new problems in the algorithm and modeling domains as we continue to push our technology forward.
  • Can work in a fast-paced environment.

Preferred Qualifications

  • Experience with dynamic pricing and/or reinforcement learning.
  • Familiar with deep learning techniques and experience with at least one DL framework (e.g. TensorFlow, PyTorch).
  • Experience working in a product and/or business-driven environment.
  • Software development experience in a production environment is a plus.
  • Experience with machine learning systems is a plus.

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