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Specialist, Data Science and Analytics (with Engineering Focus)

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Analyze delivery routes, driver efficiency and costs to optimize logistics operations

  • Build and maintain ETL/ELT pipelines that load operational data into analytics platforms

  • Design and manage SQL database schemas and data warehouses

  • Build and maintain KPI dashboards and reports in Tableau or Power BI

  • Monitor pipeline health and fix data flow and quality issues

From the employer’s posting
Conduct in-depth analysis of logistics operations, including delivery routes, driver efficiency, and cost optimization.
Develop, maintain, and optimize ETL/ELT pipelines to ingest, transform, and load operational data into our analytical platforms.
Design and manage data schemas in SQL databases and data warehouses to ensure scalability and query performance.
Develop and maintain business analytics dashboards and reports to visualize key performance indicators (KPIs)
Monitor data pipeline health and performance, proactively identifying and resolving data flow issues and quality anomalies.

What you’ll bring

All qualifications

Core experience

  • Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn) for both data manipulation and scripting/pipeline tasks.
  • Experience with data visualization tools (Tableau, Power BI, etc.).
  • Good communication skills in English and Cantonese (written and verbal) are necessary to collaborate effectively with local and international teams.
  • Ability to work independently and as part of a team.
  • Experience with Git or another version control system.

Preferred experience

  • Bachelor's degree in Computer Science, Data Science, or a closely related technical field is highly preferred.
  • Experience with real-time data analysis is a plus.
  • Experience with spatial data analysis is highly desirable.
Qualification wording
Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn) for both data manipulation and scripting/pipeline tasks.
Experience with data visualization tools (Tableau, Power BI, etc.).
Good communication skills in English and Cantonese (written and verbal) are necessary to collaborate effectively with local and international teams.
Ability to work independently and as part of a team.
Experience with Git or another version control system.
Bachelor's degree in Computer Science, Data Science, or a closely related technical field is highly preferred. Degrees in Statistics or Mathematics are also acceptable.
Experience with real-time data analysis is a plus.
Experience with spatial data analysis is highly desirable.
Education & alternatives
Who You Are - Bachelor's degree in Computer Science, Data Science, or a closely related technical field is highly preferred. Degrees in Statistics or Mathematics are also acceptable. - Minimum of 1 year of relevant experience in data science and analytics, with demonstrated experience in data pipeline development.
Apply at Gogovan

Posting record

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Status in our records
Live
First seen by us
Sep 17, 202650 days ago
Recorded sightings
80
Last seen by us
Nov 6, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 50

Similar jobs usually come down between day 7 and day 56.

From 10,418 similar postings that came down. Coming down is not always a hire.

Gogovan is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Power BI
  • Prefect
  • Tableau
  • Airflow
  • NumPy
  • pandas
  • scikit-learn
Where the posting names them
- Expert proficiency in SQL for data querying, manipulation, and schema design/optimization. - Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn) for both data manipulation and scripting/pipeline tasks. - Experience with data visualization tools (Tableau, Power BI, etc.).
Minimum Data Engineering Support:- Develop, maintain, and optimize ETL/ELT pipelines to ingest, transform, and load operational data into our analytical platforms. - Design and manage data schemas in SQL databases and data warehouses to ensure scalability and query performance. - Monitor data pipeline health and performance, proactively identifying and resolving data flow issues and quality anomalies.
- Minimum of 1 year of relevant experience in data science and analytics, with demonstrated experience in data pipeline development. - Expert proficiency in SQL for data querying, manipulation, and schema design/optimization. - Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn) for both data manipulation and scripting/pipeline tasks.
- Perform spatial data analysis to optimize delivery routes and improve logistics efficiency. - Develop and maintain business analytics dashboards and reports to visualize key performance indicators (KPIs) and track business performance using data visualization tools (Tableau, Power BI, etc.). - Present findings and recommendations to stakeholders in a clear and concise manner.
- Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn) for both data manipulation and scripting/pipeline tasks. - Experience with data visualization tools (Tableau, Power BI, etc.). - Strong practical experience with ETL/ELT pipeline concepts and automation tools (e.g., Airflow, Prefect, or cloud-native services).
- Experience with data visualization tools (Tableau, Power BI, etc.). - Strong practical experience with ETL/ELT pipeline concepts and automation tools (e.g., Airflow, Prefect, or cloud-native services). - Good communication skills in English and Cantonese (written and verbal) are necessary to collaborate effectively with local and international teams.
- Monitor data pipeline health and performance, proactively identifying and resolving data flow issues and quality anomalies. - Automate data workflows and infrastructure setup using tools like Airflow or cloud-native scheduling services. Who You Are

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,818.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

We are seeking a highly motivated and analytical Specialist, Data Science and Analytics to join our team in Hong Kong. You will be responsible for collecting, analyzing, and interpreting large datasets while also taking on minimum data engineering responsibilities to ensure data quality and flow. You will work closely with various departments to optimize our logistics operations, improve customer satisfaction, and drive business growth through both insights and infrastructure support.


What You'll Deliver

Core Data Science and Analytics:

  • Collect, clean, and analyze large datasets from various sources (operational, customer, market data).
  • Conduct in-depth analysis of logistics operations, including delivery routes, driver efficiency, and cost optimization.
  • Analyze customer behavior and identify trends to improve customer experience and drive customer retention.
  • Perform spatial data analysis to optimize delivery routes and improve logistics efficiency.
  • Develop and maintain business analytics dashboards and reports to visualize key performance indicators (KPIs) and track business performance using data visualization tools (Tableau, Power BI, etc.).
  • Present findings and recommendations to stakeholders in a clear and concise manner.
Minimum Data Engineering Support:
  • Develop, maintain, and optimize ETL/ELT pipelines to ingest, transform, and load operational data into our analytical platforms.
  • Design and manage data schemas in SQL databases and data warehouses to ensure scalability and query performance.
  • Monitor data pipeline health and performance, proactively identifying and resolving data flow issues and quality anomalies.
  • Automate data workflows and infrastructure setup using tools like Airflow or cloud-native scheduling services. 

Who You Are

  • Bachelor's degree in Computer Science, Data Science, or a closely related technical field is highly preferred. Degrees in Statistics or Mathematics are also acceptable.
  • Minimum of 1 year of relevant experience in data science and analytics, with demonstrated experience in data pipeline development.
  • Expert proficiency in SQL for data querying, manipulation, and schema design/optimization.
  • Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn) for both data manipulation and scripting/pipeline tasks.
  • Experience with data visualization tools (Tableau, Power BI, etc.).
  • Strong practical experience with ETL/ELT pipeline concepts and automation tools (e.g., Airflow, Prefect, or cloud-native services).
  • Good communication skills in English and Cantonese (written and verbal) are necessary to collaborate effectively with local and international teams.
  • Experience with real-time data analysis is a plus.
  • Experience with spatial data analysis is highly desirable.
  • Strong analytical and problem-solving skills.
  • Ability to work independently and as part of a team.
  • Experience with Git or another version control system.

What We Offer

  • A diverse, multi-cultural team that values collaboration and innovation.
  • Opportunities for continuous learning and professional development in modern data engineering tools.
  • The chance to build the data foundation that powers impactful business decisions.
  • Contribute to the growth of a leading technology-driven logistics platform in Asia.
  • Work on an exciting and high-impact product used by thousands of users.
  • Opportunity to work with cutting-edge technologies and shape data infrastructure.
  • Dynamic and international work environment.
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Location & working pattern

Hong Kong

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