Data Scientist II - Analysis, Lifecycle

talabat; Dubai; On-site; AED 60,000 - 100,000; Full time

Job summary

An established industry player is seeking a skilled Data Scientist to enhance decision-making through actionable data insights. In this pivotal role, you will manage the entire data value chain, from logging to analysis, and collaborate with cross-functional teams to drive product and business strategies. Your expertise in Python or R, along with a strong grasp of data modeling and statistical techniques, will be essential in transforming complex business challenges into clear, data-driven objectives. If you're passionate about leveraging data to make a significant impact, this opportunity is perfect for you.

Qualifications

• 3+ years of experience in data science and machine learning.
• Strong problem-solving skills and growth mindset.
• Experience with online consumer products is a plus.

Responsibilities

• Transform ambiguous business problems into data-driven objectives.
• Collaborate with teams to formulate key questions for analysis.
• Design and analyze experiments for product improvements.

Skills

Python

R

Data Modeling

Statistical Techniques

Machine Learning

Data Analysis Lifecycle

BigQuery

Google Cloud Platform

Data Pipelines

Experiment Design

Education

Bachelor's Degree in Engineering

Postgraduate Degree

Tools

Airflow

Scikit-learn

XGBoost

LightGBM

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 data scientist on the analysis track, your mission will be to improve the quality of decisions made across product and business through relevant, reliable, and actionable data. You will own a specific domain within product and business, working closely with managers and a team of data scientists and engineers. Your responsibilities include managing the entire data value chain: logging, data modeling, analysis, reporting, and experimentation.

What’s On Your Plate?

• Transform ambiguous business problems into data-driven objectives.
• Develop a deep understanding of your focus area’s product experiences and business processes.
• Familiarize yourself with source data and systems through documentation, collaboration with engineering teams, and data profiling.
• Contribute to designing and maintaining data models to measure performance and identify drivers.
• Collaborate with product and business teams to formulate key questions for data analysis.
• Deliver relevant and actionable insights via analysis and automated reports.
• Design and analyze experiments (A/B and multivariate tests).
• Support KPI development and goal setting for product and business managers.
• Mentor fellow data scientists.
• Help improve workflows, tools, and training programs.

What Did We Order?

Technical Experience

• Proficiency in reproducible data analysis using Python or R.
• Experience with data modeling and dimensional design.
• Strong command over the full data analysis lifecycle: problem formulation, auditing, analysis, interpretation, and presentation.
• Knowledge of various analysis types: descriptive, exploratory, inferential, causal, and predictive.
• Understanding of experiment design and statistical techniques.
• Familiarity with product data (impressions, events, etc.) and health metrics (conversion, engagement, retention).
• Experience with BigQuery and Google Cloud Platform is a plus.
• Experience with data pipelines (e.g., Airflow) and ML frameworks (e.g., Scikit-learn, XGBoost, LightGBM) is a plus.

Desired Candidate Profile

Qualifications

• Bachelor’s degree in engineering, computer science, or related fields; postgraduate degree is a plus.
• At least 3 years of experience in data science and machine learning.
• Experience in online consumer products is a plus.
• Strong problem-solving skills and growth mindset.
• Ownership and accountability mindset.
• Practical, straightforward approach to execution (#makeithappen).

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