[What you will be working on]

1. Project Management

a. Project manage and work closely with vendors and internal stakeholders to deliver on data related implementations ensuring that deliverables and objectives are met within agreed scope and timelines.

b. Collaborate with cross-functional teams, including data scientists, data engineers, DevOps engineers, product managers, business analysts and business stakeholders, to develop and deploy data solutions into analytics platforms and production systems.

c. Plan, execute and monitor project milestones and ensure timely update to management on project progress and issues.
 

2. Data Analysis and Insights

a. Conduct in-depth analysis to identify travel & visitor trends, patterns, and insights, including cross-datasets analyses.

b. Perform advanced analysis (e.g. predictive analytics and unstructured data analysis) and ad-hoc analytics, reporting and data visualisations relevant to project needs.

c. Collaborate with various stakeholders to communicate and refine findings & insights, so as to lead to actionable recommendations and outcomes.

d. Develop new data visualisations and enhance existing reports and dashboards.
 

3. Developing Data Solutions

a. Work with stakeholders to gather and document requirements for new data / machine learning initiatives or enhancements to existing data / machine learning pipelines.

b. Work closely with data science team and business stakeholders to identify, define, ingest and process data from multiple sources in support of analytics / ML model development.

c. Work with other large, complex datasets and solve non-routine analysis problems, applying advanced analytical methods as required.

d. Design and develop visualizations that empower users with actionable insights. Utilize best practices in data visualization to ensure clarity, engagement, and effective communication of data, and refine visualization using agile approach for optimal user experience.
 

4. Data Solution Quality Management

a. Monitor migrated data and developed pipelines / solutions, that they continue to perform as expected, including tracking of data quality scores.

b. Support the testing and validation of fixes and enhancements where required.
 

5. Data Solution Testing

a. Collaborate with vendor and internal development teams to understand product functionalities, developed data solutions and data migration approach, ensuring comprehensive testing coverage.

b. Review test plan & test cases that confirm solution requirements and data accuracies, and ensure that invalid, unexpected inputs or conditions are effectively handled.

c. Execute test plans to ensure that data solutions meet quality standards before deployment.

d. Identify, document, and track bugs and issues, through to resolution, working closely with vendor to prioritize fixes.
 

6. Data Capability Development

a. Adopt best data practices, including appropriate use of data and data governance are upheld across data initiatives.

b. Develop and carry out internal training programs aimed at improving the data and visualization capabilities of staff within the organization.

[What we are looking for]

• Strong project management, planning, time management and organisational skills.

• Good command of written and spoken English with ability to communicate complex ideas, data / concepts and outcomes of analysis clearly to business audiences.

• Experience supporting and working with cross-functional teams in a dynamic, fast-paced environment.

• Experience working with large datasets, and proficient in statistical programming tools (e.g., R), and database scripting languages (e.g., SQL), including data retrieval via APIs.

• Experienced data pipeline builder and data wrangler who enjoys optimising data processes and building them from ground up would be advantageous.

• Experience in using Qlik Sense and AWS services (e.g., SageMaker, RDS) will be advantageous.

• Degree from a recognised university in a quantitative or engineering discipline: Computer Science, Computer Engineering, Informatics / Information Systems, Applied Mathematics or Statistics.

• At least 5 years of work experience in a related field with demonstrable skills in developing, deploying and maintaining data solutions.

• Proven track record in managing internal and external stakeholders and delivering on objectives according to project timelines; and successfully involved in at least 1 medium to large scale analytics system.

• Strong analytical skills with a good eye for detail and possess an aptitude/experience in solving engineering problems to produce quality deliverables.

• Ability to integrate and synthesise research and data across multiple sources to derive meaningful conclusions.

• Experience working with structured and unstructured datasets is essential.

• Proficient in statistical programming tools (e.g., R, Python), and database scripting languages (e.g., SQL - DQL, DML, DDL)

• Experience with DataOps and/or MLOps and deploying models and data workflows through DevOps process will be advantageous.