The Data & Research Analyst is expected to develop and maintain data models that support informed, strategic decision-making. The ideal candidate will proactively identify opportunities to streamline and enhance both internal and external reporting processes. A solid grasp of regulatory and reporting requirements is essential, along with proven experience in forecasting, budgeting, and financial analysis. An in-depth understanding of key performance indicators and their impact on event and business performance is critical to success in this role. The role requires a strong understanding of, and the ability to effectively coordinate across, all DP World Group divisions—including Ports and Terminals, Maritime Services, Logistics, and Digital Technology—to support event logistics initiatives
KEY ACCOUNTABILITIES:
- Provide analytical support and insights across Event Logistics operations, sales and marketing functions
- Monitor and communicate KPIs, collaborating with relevant teams to drive continuous improvement
- Generate daily and monthly reports, including operational summaries, sales dashboards, yield performance, and event-specific logistics reports
- Develop and maintain efficient reporting systems to deliver timely, actionable insights that support strategic decision-making in event planning and execution
- Apply project management principles to support operational improvements, enhance logistical efficiency, and identify opportunities for cost savings within event delivery
- Actively contribute to business and logistics meetings, offering insights and data-driven recommendations to enhance event performance
- Present ad hoc reports as and when required
Act as an ambassador for DP World at all times when working; promoting and demonstrating positive behaviours in harmony with DP World’s Founder’s Principles, values and culture; ensuring the highest level of safety is applied in all activities; understanding and following DP World’s Code of Conduct and Ethics policies
Perform other related duties as assigned
QUALIFICATIONS, EXPERIENCE AND SKILLS:
7 to 8 years of experience in Data Engineering / Data Science / Data Analysis
A Bachelors’ or Masters’ degree in IT / Computer Science or related field
Programming languages: Well-versed and proven experience with programming languages like Python, SQL, Spark.
Statistics & Mathematics: Strong understanding of probability, statistical tests, and hypothesis testing.
Databases: Strong understanding of Delta/Data Lake or SQL Database
Cloud / Platform – Experience on Azure Cloud and Databricks is must.
Required Skills – Experience on Web Scraping, Rest APIs, LLMs, RAG applications and Agent Framework
Data visualization: Experienced with visualization tools like Matplotlib, Seaborn, Tableau, Power BI, or Plotly.
Proven experience in eliciting requirements and governing the project lifecycle
Experience in analysing data to draw business-relevant conclusions and in data visualization techniques and tools
Basic knowledge in generating process documentation
Strong written and verbal communication
