Senior Data Analyst

at  Kitopi

Kitopi is the world’s leading tech-powered multi-brand restaurant. With a mission to satisfy the world’s appetite, Kitopi operates a portfolio of both invested and franchised F&B brands, serving as enablers in the food market by helping brands to grow and scale, both in the delivery and dine-in space.
Launched in Dubai, UAE in January 2018, Kitopi has grown to become one of the greatest success stories in the cloud kitchen and food tech space. In July 2021, Kitopi announced its $415 million Series C funding round, led by the world’s largest technology-focused investment fund, Softbank Group Corp’s Vision Fund 2. This investment catapulted Kitopi to the prestigious Unicorn status, making it the fastest Unicorn to have emerged from the MENA region.
As a leading food-tech business, Kitopi’s growth has been largely fueled by its innovative and scalable software solutions. Kitopi’s kitchens are powered by its proprietary Smart Kitchen Operating System (SKOS) - an in-house suite of applications that optimizes cloud kitchen operations in real-time. As part of its growth roadmap, technological innovation, data science, artificial intelligence, and robotics will take center stage as Kitopi continues to reinvent the food industry as we know it today.
With over 4,000 employees, Kitopi currently operates 200+ locations across the UAE, KSA, Kuwait, Bahrain, and Qatar, and runs its engineering hub in Krakow, Poland, its robotics hub in Denmark, and its global customer experience center in Dubai, UAE.
Together with the Product, Engineering, Data, AI, and Robotic departments, we are creating various applications starting from highly personalized selling apps (web & mobile), through the kitchen management system, customer service, delivery, control, and business applications which help us to make decisions and determine the further direction of product development and more. We currently have around 40 applications in microservice architecture and we will constantly be creating new ones.
At Kitopi, we offer a diverse suite of brands designed to cater to the unique taste preferences of our customers. A lot of art and effort goes in the careful design and curation of our brands and menus, ensuring they are appealing and enticing to our customers. As a Senior Data Analyst at Kitopi, you will play a pivotal role in leveraging data to drive strategic decision-making and deliver impactful insights.Your expertise will contribute to expanding the brand reach, optimize customer acquisition and retention, and maximize growth and engagement. Join our dynamic team and use your advanced analytical skills to shape the future of the food tech industry

• In brief:
• Data-driven decision-making across Utilize advanced statistical analysis techniques to extract actionable insights and provide informed recommendations to stakeholders, enabling data-driven decision-making within the Brand & Growth vertical.
• Data enrichment: Collaborate with the data team to contribute to the development and enhancement of data resources. Ensure data accuracy, completeness, and quality by implementing robust data management processes and performing data validation and cleansing. Drive initiatives to enrich existing data sources and identify new data opportunities.
• Brand and marketing strategies: Collaborate closely with business and product partners to leverage data in the development of brand and marketing strategies. Utilize data analysis and insights to identify growth opportunities, optimize product improvements, and drive impactful marketing campaigns. Measure and analyze campaign performance, track key metrics, and provide actionable recommendations to enhance brand awareness, customer engagement, and retention.

In detail:

• Act as a trusted advisor to stakeholders, providing guidance on the feasibility and potential impact of different analytical approaches. Collaborate with them to understand their needs and gather requirements. Translate these requirements into clear and concise analytical problem statements, ensuring alignment between data analysis objectives and organizational goals.
• Utilize critical thinking and advanced analytical skills to generate hypotheses that address the identified business problems.
• Evaluate and select the most suitable hypotheses to focus on, considering available data, resources, and potential impact on business outcomes.
• Work collaboratively with business stakeholders, cross-functional teams, and fellow data professionals to gain context and understanding for effective problem-solving.
• Engage in active discussions, gather insights from different perspectives, and leverage collective expertise to identify opportunities and develop data-driven solutions that align with the organizational objectives.
• Collaborate with the development team, including UX/UI designers, product managers, and developers, to ensure accurate data tracking, tagging, and instrumentation. Implement data collection strategies to capture relevant user interactions and events, ensuring data integrity and quality.
• Apply advanced statistical analysis techniques to support experimentation and derive meaningful insights from data.
• Use data-driven methodologies to evaluate options, trade-offs, and set performance targets.
• Apply predictive modeling and forecasting techniques to identify trends and make informed predictions for business planning and decision-making.
• Assess the impact and value of initiatives through ROI analysis.
• Quantify the return on investment for projects, marketing campaigns, and other initiatives, providing insights into their effectiveness and guiding future decision-making.
• Develop frameworks and methodologies for measuring and evaluating the success of data-driven initiatives.
• Utilize data visualization tools and techniques to effectively communicate complex findings to both technical and non-technical audiences.
• Create visually appealing and informative dashboards to provide visibility into operational metrics and key performance indicators.
• Analyze complex datasets to extract actionable insights. Identify trends, patterns, and relationships within the data, providing valuable insights for business decision-making.
• Conduct deep-dive analysis to understand customer behavior, product performance, market trends, and other relevant factors that drive business outcomes.
• Communicate findings and recommendations in a clear and concise manner to both technical and non-technical audiences. Tailor the presentation of complex analytical concepts and results to ensure effective knowledge transfer and decision-making support.
• Ensure all projects, data sources, dictionaries, transformation processes, analyses, and findings are clearly documented, organized, and continuously updated.
• Contribute to the knowledge base by sharing insights, best practices, and lessons learned, fostering a culture of documentation and knowledge sharing.
• Collaborate with the data team to develop and maintain data governance standards and data quality assurance processes.