Specialist - Commercial Data Intelligence Almosafer

Responsibilities:

• Data Exploration & Analysis
• Explore and analyze in-house datasets (transactional, sourcing, connectivity, competitive intelligence) to generate meaningful insights
• Conduct deep-dive and ad-hoc analyses to identify trends, patterns, and opportunities that drive revenue and margin improvement
• Design and evaluate test scenarios to validate hypotheses and maximize the value of internal systems.

Insight Generation & Communication

• Translate data findings into clear, concise, and actionable insights and business recommendations
• Present analysis to stakeholders in a compelling narrative, using visualizations and storytelling to support strategic decisions
• Deliver Insights to a wider audience and reiterate to generate impactful results & achieve regular success.

Data Product Support & Continuous Improvement

• Contribute to the development and evolution of Commercial Data Products by providing insights,ntesting hypotheses, and validating assumptions
• Help shape KPIs, reporting metrics, and dashboards aligned with business goals
• Proactively suggest opportunities for optimization and process improvement using data insights
• Stay up to date with industry trends and analytics tools to enhance analytical capabilities

Stakeholder Engagement

• Collaborate closely with cross-functional teams (Sourcing, Revenue Management, Product, Sales & Marketing) to understand their data needs and deliver impactful analytical solutions
• Act as a mutual data partner, and advisor to cross-functional teams and multiple stakeholders

Advanced Analytics & Data Solutions

• Design scalable, automated analytics solutions using tools such as SQL, Python, and cloud- based data platforms to support operational analytics
• Ensure adherence to enterprise data governance and quality standards, working closely with Data Engineering and Governance teams

Collaboration & Data Governance

• Bridge Operations and Data Intelligence to ensure aligned data standards and methodologies
• Drive data literacy and analytical best practices across teams