Description

Business Analyst / Project Manager with experience in the AI-powered pharmaceutical

sector, CRM and AI integration. Successfully led data-driven initiatives,

collaborated with cross-functional teams, and delivered strategic

insights to enhance product performance and client engagement

Industry field of expertise

Languages

English
Native or bilingual
Arabic
Basic
Italian
Native or bilingual
Spanish
Conversational
French
Fluent

Workplace preferences

Can work on-site

Dubai City (up to 50km)

Cloud Science Labs
Business Analyst
September 2024 - May 2025 (8 months)
Dubai, United Arab Emirates
• Optimised CRM systems for faster retrieval of crucial business information for clients.
• Leveraged machine learning algorithms, enhancing predictive analytics capabilities.
• Streamlined data processing to enhance operational efficiency.
• Led team in designing and testing artificial intelligence systems, enhancing product quality.
• Integrated AI technology into existing software applications, improving functionality.
• Enhanced user experience by introducing intuitive AI-based features into application design.
Achiive Ltd
Business Analyst
March 2024 - August 2024 (5 months)
Winchester, England, United Kingdom
• Supported the implementation and rollout of AI-driven solutions in global oncology operations.
• Conducted process analysis and facilitated the transition to new AI-powered operating models.
• Developed dashboards and reports using Power BI and Tableau for SteerCo-level presentations.
• Collaborated with cross-functional teams to refine workflows and enhance customer-facing AI tools.
• Conducted change impact analysis to optimize adoption by end-users, including customer service agents.
Nationwide Building Society
Business analyst
January 2023 - March 2024 (1 year and 2 months)
London, UK
• Performed requirements analysis / documenting user stories and use cases
• Documentation and communication of insights and plans to cross functional team members and management
• Translate business requirements into structured data science use cases (e.g., BRDs, EPICs, User Stories)
• Served as liaison between stakeholders and users - often between technology providers and clients