[What you will be working on]

1.Project Management
a) Project manage, 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 such as data scientists, data engineers, DevOps engineers, product managers, business analysts, to define, 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) Support data scientists in conducting in-depth analysis to identify travel & visitor trends, patterns, and insights, including cross-datasets analyses and ad-hoc analytics
b) Perform advanced analysis (e.g. predictive analytics and unstructured data analysis) and ad-hoc analytics, reporting and data visualisations as relevant.
c) Design and develop new interactive dashboards and/or enhance existing visualisations while adhering to best practices, working closely with users to optimise their experience and support data-driven decision making.

3. Develop and Maintain Data Solutions
a) Participate in the development and implementation of data solutions by engaging and gathering user requirements, analysing business needs, and documenting specifications for data products and analytics solutions.
b) Review solution designs, implementation and migration approaches, ensuring alignment with business requirements.
c) Develop, monitor and maintain data pipelines and solutions, tracking data quality metrics and implementing improvements where needed.
d) Support the testing and validation of fixes and enhancements where required, including executing test cases, validating data accuracy, and monitoring system performance post-deployment.

 

[What we are looking for]

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

-Strong analytical skills with a good eye for details.

-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.

-Proven track record in managing internal and external stakeholders and delivering on objectives according to project timelines.

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

-Experience as data pipeline builder and data wrangler, optimising data processes and building them from ground up would be advantageous.

-Experience in using Qlik Sense, QuickSight and/or other AWS services (e.g., Glue, SageMaker, RDS) will be advantageous.

-Trained in a quantitative or engineering discipline: Computer Science, Informatics / Information Systems, Data Analytics, Statistics, Applied Mathematics or a related discipline.

-At least 3-5 years of Project Management experience successfully managing both internal stakeholders and external vendors.

-Proven track record in managing vendors and delivering on objectives according to project timelines; and involved in the successful implementation of least 1 medium to large scale analytics system.

-Strong planning, organisational, and time management skills

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

-Good command of written and spoken English with good presentation and communication skills with ability to express complex ideas, data / concepts and outcomes of analysis clearly to business audiences.

-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)

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