Senior Data Scientist - AI & Machine Learning

About Talabat

Established in 2004 in Kuwait, Talabat is a top on-demand food and quick-commerce platform serving customers in eight regional markets. Our deep local insights drive convenience and dependability for customers, streamline operations for restaurants and shops, and empower delivery partners with everyday earning opportunities. To support our growth and impact, we foster a dynamic culture with over 6,000 employees committed to innovation and excellence, recognized as a multi "Great Place to Work" award winner.

Job Overview

As the leading delivery service in the region, Talabat is focused on advancing intelligent technology solutions to enhance the experiences of millions of customers, restaurant partners, and riders. We are seeking a Senior Data Scientist specializing in AI and machine learning to join our global AI hub. This role involves full ownership of end-to-end machine learning systems that influence product and business decisions. Collaborating closely with product and business stakeholders, the candidate will develop generative AI and LLM-driven tools for data enrichment, content analysis, and automated decision-making, thereby improving user engagement and operational efficiency at scale.

Key Responsibilities

• Translate complex, ambiguous business challenges into well-defined machine learning problems with measurable success criteria.
• Deliver impactful insights and data-driven recommendations by conducting thorough analyses and automated reporting to guide strategic decisions.
• Design, develop, and deploy comprehensive machine learning and generative AI systems covering data pipelines, feature engineering, model training, serving, and ongoing monitoring in production environments.
• Lead engineering-intensive efforts, including architecting scalable ML systems and writing clean, maintainable production code.
• Train, evaluate, and refine models by choosing effective algorithms and architectures to maximize business value.
• Utilize large language models and generative AI for enhancing data quality, understanding content intelligently, and enabling automated decision processes within live systems.
• Maintain and improve data models, feature sets, and pipelines that underpin model training and performance tracking.
• Design and analyze rigorous experiments such as A/B and multivariate testing to evaluate the impact of models and products.
• Develop deep expertise in source datasets and their generating processes through documentation and collaboration with engineering teams.
• Partner with product and business teams to spot impactful opportunities and craft ML-based solutions along with practical data-driven insights.
• Mentor junior data scientists, fostering their professional growth.
• Advance engineering and machine learning best practices by enhancing workflows, tooling, MLOps, and training programs.

Required Qualifications and Experience

• Extensive expertise in machine learning, generative AI, deep learning, recommendation engines, natural language processing, pattern detection, and data mining.
• Proficient with ML and GenAI frameworks such as Scikit-learn, XGBoost, LightGBM, CatBoost, SVM, Keras, TensorFlow, PyTorch, Transformers, and fine-tuning large language models.
• Strong foundation in software engineering including data structures, algorithms, general system design, and ML system architecture.
• Demonstrated experience deploying, serving, and monitoring production ML models with solid understanding of MLOps practices.
• Advanced abilities in data and ML engineering including building data pipelines and robust feature engineering, preferably using workflow orchestration tools like Airflow.
• Expertise in SQL and reproducible Python-based analysis and modeling.
• Sound knowledge of statistics, experiment design (A/B and multivariate), and causal inference methods.
• Familiarity with data modeling techniques and dimensional schema design.
• Comprehensive knowledge of the entire machine learning lifecycle from problem definition to deployment and evaluation.
• Working knowledge of product data metrics (impressions, events) and product health indicators (conversion, retention, engagement).
• Experience with LLMs and NLP solutions for data enrichment and automation is advantageous.
• Familiarity with BigQuery and Google Cloud Platform is a plus.

Educational Background

Bachelor's degree in Engineering, Computer Science, Technology, or related fields is required. Postgraduate qualifications are preferred but not mandatory.

Additional Requirements and Soft Skills

• Minimum of 5 years' experience in data science, ML engineering, and generative AI with proven record of shipping models to production.
• Experience working with online consumer product systems is beneficial.
• Strong problem-solving skills and a growth mindset focused on finding solutions.
• Excellent collaboration and communication abilities.
• Demonstrates ownership, accountability, and a pragmatic attitude towards execution and simplicity.