Sr. Data Scientist - Analysis (Logistics & QC)

Company Description

Job Description

• As the leading delivery company in the region, we have 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 Senior Data Scientist supporting our Logistics and QCommerce domains, you will drive high-impact decision-making across business functions through data-driven insights and experimentation.
• Partnering closely with Business Leaders, and fellow Data professionals, you will take ownership of a key business area and influence strategy through rigorous analysis and measurement.
• Your scope will span the full data lifecycle, from instrumentation and data modeling to analytics, reporting, experimentation, and delivering actionable recommendations that drive measurable business outcomes.
• 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, interacting with the engineering teams, and systematic data profiling.
• Contributing heavily to the design and maintenance of the data models that allow us to 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.
• **Qualifications** **Technical Experience**
• Excellent SQL.
• Competence with reproducible data analysis using Python or R.
• Familiarity with data modeling and dimensional design.
• Experience designing and analyzing experiments using A/B testing, multivariate testing, switchback experiments, and synthetic control methods.
• 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 the various experiment design and analysis workflows and the corresponding statistical techniques.
• Familiarity with product data (impressions, events, ..) and product health measurement (conversion, engagement, retention, ..).
• 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.
• 5+ years of overall experience working in data science and machine learning.
• Experience doing data science in an online consumer product setting is a plus.

**Additional Information** **What We'll Be Looking For**

• Throughout the interview process, we'll assess not only your technical expertise and problem-solving abilities, but also the behaviors that drive success at talabat:
• **Own It** : Taking accountability, demonstrating initiative, and driving outcomes end-to-end.
• **Deliver Value Fast:** Balancing speed and quality to create meaningful business impact.
• **Dive Deep:** Approaching problems with curiosity, analytical rigor, and a strong attention to detail.
• **Bring Good Vibes:** Building strong relationships, collaborating effectively, and contributing positively to team culture.
• **Raise the Bar:** Striving for excellence, challenging assumptions, and continuously improving the quality of your work.
• **Stay Humble:** Remaining open to feedback, learning from others, and embracing a growth mindset.