About the job
Company Description
As the region’s leading local tech organization, we’re proud to say that we have been delivering for millions of people right across MENA for the past 18 years. We were founded in Kuwait in 2004, and acquired by Delivery Hero (DHER) in 2015. This gives us a unique outlook - local knowledge with global expertise. It also allows us to innovate, create, and bring new technologies for the betterment of the MENA region, such as q-commerce, sustainable packaging, cloud kitchens, autonomous delivery vehicles, robots, and drones. We deliver across 9 countries with more than 4,500+ employees! Our food delivery business works with over 27,000 brands and almost 50,000 branches. Our q-commerce concept, talabat mart (121 Stores), now delivers groceries to customers in Bahrain, Iraq, Egypt, Jordan, Kuwait, Oman, Qatar, and the UAE in 30 minutes or less! talabat is part of the Delivery Hero Group, the world’s leading local delivery platform operating in 70+ countries worldwide.
Job Description
Role Summary
As a Senior Manager leading the Logistics Data Science Unit, you will play a crucial role in elevating the decision-making processes across our business landscapes through insightful, reliable, and actionable data analytics. You will oversee multiple domains within our logistics, vendor, and delivery operations, collaborating closely with business leaders, and a dynamic team of data scientists and engineers. Your leadership will ensure the seamless integration of the data value chain—from data collection and modeling to analysis, reporting, and experimentation—ultimately empowering Talabat to achieve operational excellence and unparalleled customer satisfaction.
What’s On Your Plate? Responsibilities:
- Lead the strategic vision for harnessing data to refine and enhance logistics operations. This involves identifying key opportunities for process optimization, cost reduction, and service quality improvements, ensuring that data science initiatives are perfectly aligned with Talabat’s broader business goals.
- Champion the adoption of a data-driven culture within logistics operations, emphasizing the importance of basing decisions on rigorous data analysis and actionable insights. This includes promoting the use of advanced analytics and data science methodologies across all levels of logistics operations.
- Build and maintain strong collaborative relationships with key stakeholders across product, business, and engineering teams. Ensure that data science projects are integrated with and supportive of overall business strategies, fostering a cohesive approach to achieving Talabat’s objectives.
- Guide, mentor, and develop a highly skilled team of data scientists and data analysts. Set clear performance goals, facilitate professional development opportunities, and foster a supportive and innovative work environment that attracts top talent.
- Spearhead innovative data science projects, including the application of predictive analytics, machine learning models, and optimization algorithms. Focus on projects that have the potential to significantly impact logistics efficiency and customer satisfaction.
- Ensure the development and maintenance of a robust and scalable data infrastructure that supports advanced analytics and data science activities. This includes advocating for best practices in data governance, quality control, and compliance with relevant data protection regulations.
- Oversee the generation of insightful analytical reports and dashboards that track key performance indicators (KPIs) and provide strategic insights to both the logistics team and senior management. Ensure that these insights are actionable and contribute to informed decision-making processes.
- Serve as a key point of communication between the data science unit and both internal and external stakeholders. Translate complex data-driven insights into clear, understandable, and actionable recommendations for various audiences.
- Stay abreast of the latest trends and advancements in data science, logistics, and technology. Incorporate cutting-edge practices and tools into Talabat’s data science strategy to maintain a competitive edge and foster continuous improvement.
- Effectively manage resources and priorities to strike a balance between long-term strategic initiatives and immediate operational needs. Ensure that the data science team’s efforts are focused on projects with the highest potential for positive impact on Talabat’s operations.
- Design, implement, and manage experimental frameworks, such as A/B testing, to validate new ideas and measure their impact on logistics performance. Use these insights to guide continuous improvement efforts.
- Provide expert analytical support to cross-functional teams, assisting in the development of KPIs and goal-setting processes that align with Talabat’s strategic objectives.
- Lead by example to cultivate an environment of excellence and innovation within the data science team. Encourage creative thinking, continuous learning, and the exploration of new ideas to drive forward Talabat’s logistics operations.
Qualifications
Technical Expertise:
- Proficient in the full data analysis lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, and presentation.
- Advanced skills in data analysis tools and programming languages such as Python, R, and SQL.
- Demonstrated expertise in data modeling, dimensional design, and the ability to understand and manipulate complex data structures.
- Strong background in experiment design and statistical analysis, capable of conducting and analyzing A/B and multivariate tests.
- Knowledge of Big Data technologies, preferably with experience in BigQuery and the Google Cloud Platform.
- Experience in data engineering and pipeline development, e.g., through tools like Airflow, is highly regarded.
- Familiarity with classical machine learning frameworks (e.g., Scikit-learn, XGBoost, LightGBM) is advantageous.
Qualifications:
- Bachelor's or Master's degree in Engineering, Computer Science, Technology, or related fields. An advanced degree is preferred.
- A minimum of 8+ years of experience in data science, with at least 3+ years in a leadership role managing data teams or operations.
- Proven leadership ability in managing diverse, high-performing teams and in developing and executing strategic plans to meet business objectives.
- Exceptional collaboration and communication skills, capable of guiding, influencing, and persuading a wide range of stakeholders.
- Demonstrated problem-solving skills with a growth mindset, able to tackle complex challenges and drive forward innovative solutions.
- A strong sense of ownership and accountability, coupled with a commitment to delivering high-quality results.
