As the leading delivery company in the region, talabat has a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in how it understands and serves our users. As a data scientist on the analysis track, your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain including logging, data modeling, analysis, reporting, and experimentation.
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Location: Dubai, UAE
Job Type: Full-time
What’s On Your Plate?
- Leveraging ambiguous business problems as opportunities to drive objective criteria using data.
- Developing a deep understanding of the product experiences and business processes that make up your area of focus.
- Developing a deep familiarity with the source data and its generating systems through documentation and interaction with engineering teams.
- Contributing heavily to the design and maintenance of the data models that measure performance and comprehend performance drivers for your area of focus.
- Working closely with product and business teams to identify important questions that can be answered effectively with data.
- Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision making through deep analysis and automated reports.
- Designing, planning and analyzing experiments (A/B and multivariate tests).
- Supporting product and business managers with KPI design and goal setting.
- Mentoring other data scientists in their growth journeys.
- Contributing to improving our ways of work, our tooling, and our internal training programs.
Requirements
- Excellent SQL skills.
- Competence with reproducible data analysis using Python or R.
- Familiarity with data modeling and dimensional design.
- Strong command over the entire data analysis lifecycle including; problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.
- Familiarity with different types of analysis including; descriptive, exploratory, inferential, causal, and predictive analysis.
- Deep understanding of various experiment design and analysis workflows and corresponding statistical techniques.
- Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).
- Familiarity with BigQuery and the Google Cloud Platform is a plus.
- Data engineering and data pipeline development experience (e.g. via Airflow) 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 similar fields. A postgraduate degree is a plus but not required.
- 3+ years of overall experience working in data science and machine learning.
- Experience doing data science in an online consumer product setting is a plus.
- A good problem solver with a ‘figure it out’ growth mindset.
- An excellent collaborator and communicator.
- A strong sense of ownership and accountability.
- A ‘keep it simple’ approach to achieving outcomes.
Company Overview
Since launching in Kuwait in 2004, talabat has become the leading on-demand food and Q-commerce app for everyday deliveries, offering convenience and reliability to its customers. With roots in the local community, talabat understands the needs of the regions it serves in eight countries. The company harnesses innovative technology to simplify everyday life for customers, optimize operations for restaurants and local shops, and provide riders with reliable earning opportunities. At talabat, employees are encouraged to create a positive impact across the region through the use of its platform.
