As the leading delivery company in the region, talabat carries the responsibility to impact millions of customers, restaurant partners, and riders. We aim to advance our platform to enhance our understanding of and service to our users.
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As a data scientist on the analysis track, you will focus on improving the quality of decisions made across product and business operations through relevant, reliable, and actionable data. You will own a specific domain within product and business, collaborating closely with product managers and business managers as part of a talented team of data scientists and data engineers. You will oversee the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.
Key Responsibilities:
- Convert ambiguous business problems into opportunities using data.
- Develop a deep understanding of product experiences and business processes in your area.
- Familiarize yourself with source data and its generating systems through interaction with engineering teams and systematic data profiling.
- Contribute to the design and maintenance of data models for measuring performance and understanding performance drivers.
- Collaborate with product and business teams to pose and answer important questions using data.
- Deliver actionable insights and recommendations to support data-driven decision-making through deep analysis and automated reports.
- Design, plan, and analyze experiments (A/B and multivariate tests).
- Support product and business managers in KPI design and goal setting.
- Mentor fellow data scientists.
- Contribute to improving workflows, tooling, and internal training programs.
Technical Experience Required:
- Excellent SQL skills.
- Competence in reproducible data analysis using Python or R.
- Experience with data modeling and dimensional design.
- Strong command of the data analysis lifecycle, including problem formulation, data auditing, analysis, interpretation, recommendations, and presentation.
- Familiarity with various analysis types (descriptive, exploratory, inferential, causal, predictive).
- Understanding of experiment design and statistical techniques.
- Familiarity with product data metrics (impressions, events) and product health measurements (conversion, engagement, retention).
- Familiarity with BigQuery and the Google Cloud Platform is a plus.
- Data engineering and data pipeline development experience is a plus.
- Experience with classical ML frameworks (e.g., Scikit-learn, XGBoost, LightGBM) is a plus.
Qualifications:
- Bachelor’s degree in engineering, computer science, technology, or a related field. A postgraduate degree is beneficial but not required.
- 3+ years of experience in data science and machine learning.
- Experience in data science within online consumer product settings is a plus.
- Strong problem-solving skills with a proactive, 'figure it out' mindset.
- Excellent collaboration and communication abilities.
- Strong sense of ownership and accountability.
- A straightforward approach to achieving results.
