As the leading delivery company in the region, talabat has a responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize its potential, talabat aims to advance its platform to become more intelligent in understanding and serving users.
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As a Data Scientist on the analysis track, your mission will be to enhance the quality of decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will collaborate closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. Responsibilities include managing the entire data value chain, from logging and data modeling to analysis and reporting.
Key Responsibilities:
- Leverage ambiguous business problems as opportunities to drive objective criteria using data.
- Develop a deep understanding of product experiences and business processes relevant to your area of focus.
- Gain familiarity with source data and its generating systems by interacting with engineering teams and conducting systematic data profiling.
- Contribute to the design and maintenance of data models that help measure performance and understand performance drivers.
- Work closely with product and business teams to identify important data-driven questions.
- Deliver actionable insights and recommendations to support data-driven decision making.
- Design, plan, and analyze experiments (A/B and multivariate tests).
- Support product and business managers with KPI design and goal setting.
- Mentor other data scientists in their professional development.
- Contribute to improving workflows, tooling, and internal training programs.
Required Technical Experience:
- Excellent SQL skills.
- Proficiency in reproducible data analysis using Python or R.
- Familiarity with data modeling and dimensional design.
- Strong command of the entire data analysis lifecycle, including problem formulation, data auditing, analysis, interpretation, and presentation.
- Understanding various types of analysis including descriptive, exploratory, inferential, causal, and predictive analysis.
- Experience with experiment design and analysis workflows with corresponding statistical techniques.
- Familiarity with product data and health measurement (such as conversion, engagement, retention).
- Knowledge of BigQuery and Google Cloud Platform is a plus.
- Data engineering and pipeline development experience (e.g., via Airflow) is a plus.
- Experience with classical ML frameworks (e.g., Scikit-learn, XGBoost, LightGBM, etc.) is a plus.
Qualifications:
- Bachelor’s degree in engineering, computer science, technology, or related fields; a postgraduate degree is a plus but not required.
- 3+ years of experience in data science and machine learning.
- Experience in data science within an online consumer product setting is preferred.
- Strong problem-solving skills with a growth mindset.
- Excellent collaboration and communication skills.
- Strong sense of ownership and accountability.
- A simplification approach to achieve goals effectively.
