Key Accountabilities
The role collaborates with stakeholders, document findings, and proposes solutions, whilst supporting international technology adoption. The role is responsible for analyzing business processes, evaluating system requirements and supporting the design and implementation of traditional and AI‑enabled solutions across the organization.
This role is ideal for someone who thrives in fast moving, cross-border environments and relishes the challenge of solving complex problems; turning data into insight and insight into action. It’s perfect for a bridge‑builder who unites teams and turns ambiguity into focused clarity, driving progress with confidence and momentum.
Job Responsibilities & Duties
Gather, document, reconcile conflicts, analyse business requirements and system goals from multiple sources (e.g., product, technology, marketing, operations). Reconcile conflicting needs translating them into clear functional specifications. Establish AI‑specific requirements where applicable, including data needs, XAI, RAI, model behavior, integration points and security.
Analyze system workflows and processes to identify improvement opportunities across automation, operational support, engineering, prediction and modern AI capabilities such as LLMs, RAG and agentic systems. Build a clear end‑to‑end view of business needs, system constraints and AI opportunities applying strong technical skills across APIs and data flows. Use a working knowledge of prompt design and model behaviour to shape requirements whilst collaborating effectively with AI engineers
Work closely with architects, developers and engineers to shape high‑quality system enhancements and integrations
Identify and resolve conflicting priorities, dependencies and constraints across teams and departments
Identify business needs and drive process improvements by working with stakeholders to determine how Business Intelligence tools can address challenges and deliver strategic, data‑driven solutions
Support change management communicating requirement updates effectively ensuring traceability through development, testing and deployment. Maintain a central repository of business requirements, change requests and release notes.
Translate complex (sometimes contradictory) inputs into unified, actionable specifications whilst acting as a mediator to drive alignment and facilitate constructive compromise
Collaborate with project managers and product owners to ensure scope clarity and delivery feasibility; whilst understanding operational pain points and translating them into software requirements
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Shape platform features such as booking flows, driver apps, payment systems and routing logic with developers and product managers.
Conduct market research and data analysis to identify trends and opportunities, recommend system enhancements and assess the competitive landscape. Develop and present process improvement plans and recommendations.
Support testing and rollout of new features across multiple environments
Ai Focus
Identify opportunities where AI, automation or advanced analytics can enhance business processes and unlock greater operational efficiency
Assess AI feasibility given data readiness, integration complexity and expected business value. Analyze data sources, data quality and data flows necessary to support system and AI requirements. Support monitoring of data quality and AI‑related data issues
Work with AI engineers and data scientists to define model inputs, outputs, and integration requirements. Validate AI model behaviour alignment of outputs with business expectations. Collaborate with data engineering teams on mappings, transformations and pipeline needs
Ensure AI use cases follow core responsible‑use guidelines (accuracy, transparency, user impact). Contribute to risk and impact assessments for new AI capabilities
Minimum Education/Qualifications
Bachelor’s degree in Computer Science, Information Systems, Business or related field
3+ years of experience in Technical System/business analysis, preferably in a matrixed or agile environment, ideally in taxi or rideshare
Experience with requirements management tools such as Jira, Confluence, Trello and data dashboards (e.g., Power BI)
Foundational knowledge of AI/ML concepts (LLMs, predictive models, , RAG, AI Agents, Agentic AI) and automation.
Strong understanding of SDLC and agile methodologies (Scrum, Kanban etc.) and practices like creating and refining user stories and writing acceptance criteria.
Understanding of cloud platforms (AWS, Azure, GCP, VMware), CI/CD pipelines, DevOps practices, and FinOps principles to enable analysis, support and optimization of cloud‑efficient workflows
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