About the Job:
talabat is part of the Delivery Hero Group, the world’s pioneering local delivery platform, with a mission to deliver an amazing experience—fast, easy, and to your door. We operate in over 70+ countries worldwide.
As a data scientist on the analysis track, your mission will be to improve 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, working closely with product and business managers as part of a talented team of data scientists and data engineers. Your responsibilities will include managing the entire data value chain—logging, data modeling, analysis, reporting, and experimentation.
Key Responsibilities:
- Leverage ambiguous business problems as opportunities using data to drive objective criteria.
- Develop a deep understanding of product experiences and business processes related to your focus area.
- 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 to measure and comprehend performance drivers.
- Collaborate with product and business teams to identify key questions that can be answered effectively with data.
- 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 and contribute to improving internal processes and training programs.
Qualifications:
- Excellent SQL skills.
- Competence in 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 various types of analysis (descriptive, exploratory, inferential, causal, and predictive).
- Understanding of experiment design and analysis workflows and corresponding statistical techniques.
- Familiarity with product data (impressions, events) and product health measurement (conversion, engagement, retention).
- Experience with 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) is a plus.
Education:
- Bachelor's degree in engineering, computer science, technology, or related fields; a postgraduate degree is a plus but not required.
- 5+ years of experience in data science and machine learning.
- Experience in an online consumer product setting is a plus.
Skills:
- Strong problem-solving and growth mindset.
- Excellent collaboration and communication skills.
- Strong sense of ownership and accountability.
- Ability to simplify complex concepts.
Language Requirements: Not specified.
This job overview serves to provide clear insights into the role and expectations, suitable for potential applicants seeking to understand the opportunity better.
