Senior Data Scientist - Logistics

Talabat; Dubai; On-site; AED 35,000 - 55,000; Full time

Job summary

Talabat is seeking a Senior Data Scientist - Logistics in Dubai. This role focuses on logistics analytics, data modeling, and experimentation for our on-demand delivery platform. Ideal candidates will possess over five years of experience in data science and machine learning.

You will collaborate with product and business teams to deliver actionable insights through complex data analysis and automated reporting. A Bachelor’s degree in a related field is required, along with strong SQL and programming skills.

Qualifications

• Minimum 5 years of overall experience in data science and machine learning.
• Experience in Q-commerce or logistics preferred.
• Excellent SQL skills for data extraction and analysis.

Responsibilities

• Convert logistics and Q-commerce problems into structured questions.
• Partner with product teams for data analysis and experimentation.
• Deliver insights and recommendations through dashboards and reports.

Skills

Data science

Logistics analytics

Q-commerce analytics

Machine learning

SQL

Python

R

Data modeling

Experiment design

Education

Bachelor's degree in Engineering, Computer Science, Data Science, or similar

Tools

BigQuery

Google Cloud Platform

Airflow

Scikit-learn

XGBoost

LightGBM

Job description

Senior Data Scientist - Logistics Job Snapshot
Role: Senior Data Scientist - Logistics
Location: Dubai, United Arab Emirates
Industry: Internet
Function: R and D-Science
Experience: 5 years in data science and machine learning
Job Type: Full-time

Job Overview

Senior Data Scientist - Logistics in Dubai, United Arab Emirates is an Internet industry opportunity focused on data science, logistics analytics, Q-commerce insights, experimentation, product data modeling, and business performance measurement for a leading on-demand delivery platform. This role is ideal for a data science professional who can turn complex logistics and Q-commerce questions into reliable analysis, measurable experiments, automated reporting, and practical recommendations that improve customer experience, operational efficiency, and platform performance.

Job Details

Country: United Arab Emirates
City: Dubai
Industry: Internet
Function: R and D-Science
Salary: 35000-55000
Gender: Any
Nationality: Any
Job Type: Full-time

Context

The Senior Data Scientist - Logistics will support key decisions across logistics and Q-commerce domains by owning the full data lifecycle, from instrumentation and source data profiling to data modeling, analysis, experimentation, reporting, and recommendation delivery. The role works closely with business leaders, product teams, engineering teams, and data professionals to answer high-impact questions using objective criteria and rigorous measurement. By building trusted analysis and scalable reporting, this position helps improve logistics reliability, Q-commerce operations, conversion, engagement, retention, and business decision quality.

Key Responsibilities

• Convert ambiguous logistics and Q-commerce business problems into structured analytical questions with clear success metrics.
• Develop deep understanding of product experiences, delivery workflows, Q-commerce processes, and business drivers within the assigned domain.
• Build strong familiarity with source data, product events, generating systems, tracking logic, and data quality limitations.
• Work with engineering teams to understand data flows, documentation, instrumentation needs, and system behavior.
• Contribute to the design and maintenance of data models that measure performance and explain key drivers across logistics and Q-commerce.
• Partner with product and business teams to identify important questions that can be answered through data, experimentation, and analysis.
• Deliver reliable insights and recommendations through deep analysis, dashboards, automated reports, and structured business reviews.
• Design, plan, and analyze experiments including A/B tests, multivariate tests, switchback experiments, and synthetic control methods.
• Support product managers and business leaders with KPI design, metric definitions, goal setting, and performance interpretation.
• Use SQL, Python, or R to perform reproducible analysis and validate findings with strong statistical discipline.
• Apply descriptive, exploratory, inferential, causal, and predictive analysis to understand customer behavior, operational performance, and product outcomes.
• Analyze product data such as impressions, events, conversion, engagement, retention, and other product health indicators.
• Identify performance gaps, operational risks, measurement issues, and improvement opportunities across logistics and Q-commerce workflows.
• Communicate analytical findings clearly to technical and non-technical stakeholders, turning complex results into decision-ready recommendations.
• Support stronger data practices by improving reporting logic, analytical documentation, data quality checks, and experimentation standards.

Ideal Profile

• Bachelor's degree in Engineering, Computer Science, Technology, Data Science, Statistics, Mathematics, or a similar field.
• Postgraduate degree is an advantage but not required.
• Minimum 5 years of overall experience in data science, machine learning, product analytics, experimentation, or advanced business analytics.
• Experience applying data science in an online consumer product, marketplace, e-commerce, Q-commerce, logistics, or delivery platform environment is preferred.
• Excellent SQL skills for data extraction, validation, transformation, and analytical modeling.
• Strong competence in reproducible data analysis using Python or R.
• Familiarity with data modeling, dimensional design, metric design, and analytical data structures.
• Experience designing and analyzing A/B tests, multivariate tests, switchback experiments, and synthetic control methods.
• Strong command of the full data analysis lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendation building, and presentation.
• Familiarity with descriptive, exploratory, inferential, causal, and predictive analysis methods.
• Deep understanding of experiment design workflows, statistical techniques, and measurement approaches.
• Familiarity with product data such as impressions, events, conversion, engagement, retention, and product health metrics.
• Familiarity with BigQuery and Google Cloud Platform is an advantage.
• Data engineering or pipeline development experience using tools such as Airflow is valuable.
• Experience with classical machine learning frameworks such as Scikit-learn, XGBoost, LightGBM, or similar tools is a plus.
• Strong ownership, collaboration, communication, and problem-solving mindset.
• Able to work with business leaders and product teams while keeping analysis simple, practical, and tied to measurable outcomes.

Skills Set

• Data science
• Logistics analytics
• Q-commerce analytics
• R and D-Science
• Machine learning
• Product analytics
• SQL
• Python
• R
• BigQuery
• Google Cloud Platform
• Airflow
• Scikit-learn
• XGBoost
• LightGBM
• Data modeling
• Dimensional design
• Experiment design
• A/B testing
• Multivariate testing
• Switchback experiments
• Synthetic control methods
• Descriptive analysis
• Exploratory analysis
• Inferential analysis
• Causal analysis
• Predictive analysis
• KPI design
• Product health metrics
• Conversion analysis
• Engagement analysis
• Retention analysis
• Automated reporting
• Dashboard insights
• Data auditing
• Source data profiling
• Business recommendations
• Stakeholder communication