Data Scientist (Analytics-focused)

Hong Kong, Hong Kong SAR

Lalamove

Lalamove is the fastest way to deliver anything in your city. From parcel courier to bulky delivery, Lalamove connects you with thousands of drivers in 1 click.

View company page

At Lalamove, we believe in the power of community. Millions of drivers and customers use our technology every day to connect with one another and move things that matter. Delivery is what we do best and we ensure it is always fast and simple. Since 2013, we have tackled the logistics industry head on to find the most innovative solutions for the world’s delivery needs. We are full steam ahead to make Lalamove synonymous with delivery and on a mission to impact as many local communities we can. We have massively scaled our efforts across Asia and now have our sights on taking our best in class technology to the rest of the world. And we are looking for talented professionals to join us in this journey!!
The Data Science Product (DSP) team is looking for a Data Scientist to join a growing team of data scientists and machine learning engineers to support different functional departments in the headquarters, as well as our offices around the Globe. As a Data Scientist at Lalamove, you will be working at the intersection of data analysis and science, drawing meaningful insights from data sets using statistical tools as well as designing data modeling processes. We tackle a multitude of exciting challenges including order allocation, OCR, fraud detection, computer vision, and many others you will help identify and resolve. If you enjoy finding patterns amidst chaos, and have experience using analytics to affect revenue, growth, operations or beyond, we’re looking for someone like you!

What we seek:

  • Quick learner: you enjoy analyzing data, and you have the ability to learn new methods and technologies quickly
  • Problem solver: you have strong critical thinking skills, willing to find creative solutions to difficult problems and work smart before hard
  • High autonomy: self-organized, initiator, passionate with a can-do attitude and own end-to-end projects
  • Team player: you go the extra mile to ensure success and alignment of all parties involved
  • Communicative: you effectively interpret insights in simple terms to inspire actions and influence the strategy of stakeholders


  • What you will do
  • Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business
  • Build full-cycle analytics experiments, reports, and dashboards using SQL, Python, or other scripting and statistical tools
  • Use statistical techniques and hypothesis testing to validate your findings 
  • Provide insights to help business and product leaders understand marketplace dynamics, user and driver behaviors

What you'll need:

  • 2+ years of work experience in a business intelligence, data analytics or data science role (fresh graduates also considered)
  • Educational background in statistics, computer science, other applied sciences or understanding of data science theory
  • Experience in applying visualization, statistical inference and other data mining techniques on variety of data
  • Solid programming skills with Python and SQL
  • Experience with ETL, A/B Testing, and statistical analysis (e.g. hypothesis testing, experimentation, regressions)
  • Experience using Tableau or other BI Tools for reporting and analyses
  • Experience with AWS services is a plus
  • Good command of English

Tags: A/B testing AWS Business Intelligence Computer Science Computer Vision Data analysis Data Analytics Data Mining ETL Machine Learning OCR Python SQL Statistics Tableau Testing

Perks/benefits: Career development

Region: Asia/Pacific
Country: Hong Kong
Job stats:  13  1  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.