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Job ref no.: CT3121554-01#0045
Ztore HK Limited 士 多

Graduate Trainee (Data Team)

Ztore HK Limited 士 多

Benefits
  • 5-day week
  • Flexible working hours

Ztore’s data team is rapidly expanding. We are looking for a 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 a all-rounded competence in utilizing data in business, and with good performance will be work as a junior data scientist, data engineer, or assistant BI manager in our team.

Responsibilities

Complete assigned tasks from supervisors in the following streams:

1.Machine Learning:

  • Take part in improving the model of our main ML application: recommender system
  • Evaluate application of ML in other use cases independently, and with guidance, productionise and deploy ML models

2. Big Data Engineering

  • Expand our current data pipeline utilizing streaming/distributed computing frameworks
  • Design data models for our data warehouse and implement ETL workflows

3. Business Intelligence

  • 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

1. Bachelor’s degree
2. Solid experience with R or Python
3. At least 2 of the followings:

  • Machines Learning: Experience in building ML models, with knowledge about advanced ML topics (neural networks, embedding, etc). Able to formulate machine learning problem from a business use case.
  • Databases: Solid knowledge in SQL queries (joining tables, sub-queries). Knowledge about NoSQL DBs is a plus
  • Data visualization: Experience using BI tools (Tableau, PowerBI, Qlik), or advanced use of visualization in R or Python (plotly, ggplot)
  • Cloud Devops:
  • Application deployment on cloud using modern tools: docker, serverless architecture, etc.

The Ideal Candidate

  • You have 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, Redis)
  • 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, Power BI)
  • Digital analytics tools (e.g. Google Analytics, Facebook Business Insights)
  • Production level programming practises (e.g. version control, error handling, deployment)

Our Stack

  • Python (tensorflow, flask), Scala, R, Node.js, Vue.js
  • Database: MySQL/DynamoDB/MongoDB/BigQuery
  • Distributed stream processing: Apache Beam/Kafka/Kinesis/Pub Sub
  • Analytics: Tableau
  • DevOps: Docker, ECS
  • Machine Learning: Recommender system, neural network, embedding, forecasting, unbalanced classification

Why us?

  • Support for learning (Opportunities to attend workshops during working hour, allowance for self-learning, and a team to grow together)
  • No legacy system to maintain
  • Casual, friendly yet supportive and motivated team culture
  • Flexibility in assigning tasks to meet your learning and career goals
  • 5-day work
  • Flexible working hour
  • Competitive remuneration

 

If you are interested, please provide your:

  • CV
  • Cover letter (optional)
  • Current and expected salary
  • Availability
  • Past projects (Github repo or other formats, optional)

More job information
Job ref no. CT3121554-01#0045
Salary
  • 14,000 - 20,000 / month
Job Function
Industry
Location
  • Lai Chi Kok
Employment Term
  • Full-time
Experience
  • 0 year - 3 years
Career Level
  • Entry level
Education
  • Degree
Require to Travel
  • No travel