Since launching in Kuwait in 2004, talabat has become the leading on-demand food and Q-commerce app for everyday deliveries, providing convenience and reliability to customers. Our local roots enable us to understand the needs of communities across eight countries in the region. At talabat, we leverage innovative technology to simplify daily life for our customers, optimize operations for restaurants and local shops, and create reliable earning opportunities for our riders.
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As a Data Scientist on the analysis track, your mission is to enhance decision-making across product and business through relevant, reliable, and actionable data. You will take ownership of a specific domain and collaborate closely with product and business managers, working within a talented team of data scientists and data engineers. Key responsibilities include managing the entire data value chain, which encompasses logging, data modeling, analysis, reporting, and experimentation.
Key Responsibilities:
- Transform ambiguous business problems into data-driven opportunities.
- Develop a comprehensive understanding of product experiences and business processes in your focus area.
- Build familiarity with source data and its systems through documentation and collaboration with engineering teams.
- Contribute to the design and maintenance of data models for performance measurement and analysis.
- Collaborate with product and business teams to identify key questions addressed by data.
- Deliver actionable insights and recommendations to support data-driven decision-making through in-depth analysis and automated reporting.
- Design, plan, and analyze experiments (A/B and multivariate tests).
- Support product and business managers with KPI design and goal setting.
- Mentor junior data scientists and contribute to internal training programs.
Qualifications:
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Technical Experience:
- Excellent SQL skills.
- Proficient in data analysis using Python or R.
- Familiarity with data modeling and dimensional design.
- Strong command of the data analysis lifecycle: problem formulation, auditing, analysis, interpretation, recommendations, and presentation.
- Knowledge of various analysis types: descriptive, exploratory, inferential, causal, and predictive.
- Familiarity with experiment design and statistical techniques.
- Understanding of product data and health measurement metrics.
- Experience with BigQuery and Google Cloud Platform is a plus.
- Data engineering and pipeline development experience (e.g., via Airflow) is a plus.
- Familiarity with classical ML frameworks (e.g., Scikit-learn, XGBoost, LightGBM) is a plus.
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Education & Experience:
- Bachelor's degree in engineering, computer science, technology, or a similar field; a postgraduate degree is a plus.
- 3+ years of experience in data science and machine learning.
- Experience in a data science role within an online consumer product setting is advantageous.
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Skills:
- Strong problem-solving skills with a growth mindset.
- Excellent collaboration and communication abilities.
- High sense of ownership and accountability.
- Ability to communicate complex concepts simply and effectively.
Language Requirements:
- Proficiency in English; additional languages are a plus.
