Utilised tools such as Python, R, SQL, and Tableau to perform data analysis and visualisation.Built predictive models using algorithms such as linear regression, decision trees, and neural networks. Participated in end-to-end data science projects, from data collection and preparation to model building and deployment. Analysed large datasets using statistical and machine learning techniques to uncover insights and make predictions. Created visualisations and presentations to effectively communicate findings to stakeholders and team members. Stayed up-to-date with the latest industry trends and techniques, including emerging technologies and tools in the field of data science. Demonstrated strong communication and interpersonal skills, presenting findings and recommendations to stakeholders and peers. Completed coursework and projects in data science, statistics, and computer science, applying theoretical concepts to real-world problems.

Assisted in conducting market research and analysis to support real estate investment decisions. Helped to prepare presentations and reports for clients, presenting findings and recommendations on real estate investment opportunities. Worked closely with senior team members to gather and analyse data on market trends, supply and demand, and economic indicators. Provided support for the management of client relationships, including conducting research and preparing materials for meetings and presentations. Developed a strong understanding of the real estate investment process, including property acquisition, financing, and asset management.

Oversaw periodic on-site projects and monitored compliance with detailed design documents. Collaborated with stakeholders for completion of construction drawings and technical details.Developed a strong sense of adaptability and managerial skills.