We (Ztore.com) are an online supermarket with same-day delivery, selling quality groceries and home essentials. You can simply buy what you want anywhere anytime online. Through our certificated payment gateway, you just choose your favorite delivery time slot and you will receive your delivery at home fast and safe.
Our vision is to Deliver A Better Living to our customers through choices that really matter and excellent service.
Ztore has an innovative and open-minded culture. Ztore blends the Traditional Values with cutting-edge technology. We develop our people by empowering them with decision-making authorities in everyday-life at Ztore.
Ztore is undergoing rapid expansion and we are looking forward to you joining our energetic and creative team. You will find out that it’s more than just a JOB.
Ztore’s data team is rapidly expanding. We are looking for bright fresh/recent graduates to join and grow with us. You will learn to use cutting edge tools in 3 different streams: 1) machine learning, 2) data engineering, 3) business intelligence. Upon completion of the 1 year programme, you will gain an all-rounded competence in the frontier of business data technology.
• Complete assigned tasks from supervisors in the following streams:
--- Machine Learning:
Take part in improving the different ML models currently in use, e.g. recommender system, fraud detection.
Evaluate application of ML in other use cases independently, and with guidance, productionise and deploy ML models
---Big Data Engineering
Expand our current data pipeline utilizing streaming/distributed computing frameworks
Design data models for our data warehouse and implement ETL workflows
Create intuitive and interactive data visualizations upon users’ requests
Organize training activities for internal teams to strengthen data competence in the company
Required Skills & Qualifications
• Bachelor’s degree in any discipline
• Solid experience with Python
• Machines Learning:
Experience in building ML models, with knowledge about advanced ML topics (neural networks, embedding, etc). Able to formulate a machine learning problem for a business use case.
• At least 1 of the followings:
Application deployment on cloud using modern tools: docker, serverless architecture, etc.
Solid knowledge in SQL queries (joining tables, sub-queries). Knowledge about NoSQL DBs is a plus
Experience using BI tools (Tableau, PowerBI, Qlik), or advanced use of visualization in R or Python (plotly, ggplot)
• Fluency in Cantonese and good written English
• Strong interest in FMCG/CRM related data problems
The Ideal Candidate
• You have a very strong sense in data
• You believe that data is the future, and wish to gain competence as quickly as possible
• You enjoy learning and using new technologies on a day to day basis
What you will learn
You will learn these on the go. It would be a plus if you already know some of them, but they are not required.
• Applying machine learning in business setting
• Distributed/streaming processing frameworks (e.g. Beam, Kafka)
• NoSQL databases (e.g. DynamoDB, MongoDB, Elasticsearch)
• Data Warehousing (e.g. BigQuery)
• Workflow management tools (e.g. Airflow)
• Developing data applications on cloud platforms (e.g. AWS, GCP)
• Containers (e.g. Docker, Kubernetes)
• BI Tools (e.g. tableau)
• Digital analytics tools (e.g. Google Analytics, Facebook Business Insights)
• Production level programming practise (e.g. version control, error handling, deployment)
• Python (tensorflow, flask), Scala, R, Node.js, Vue.js
• Database: BigQuery/DynamoDB/MySQL/MongoDB/Elasticsearch
• Distributed stream processing: Apache Flink/Beam/Kafka/Kinesis/Pub Sub
• Analytics: Tableau
• DevOps: Docker, ECS, Kubernetes
• Machine Learning: Recommender system, neural network, embedding, forecasting, unbalanced classification
• Established data team with multiple modern data/ML workloads in production
• Support for learning (Opportunities to attend workshops during working hour, allowance for self-learning and reference books)
• A passionate motivated yet friendly and casual team
• Flexibility in assigning tasks to meet your learning and career goals
• 5-day work
• Flexible working hour