Sr. Data Scientist (AI & ML)

Deliveryhero; Dubai; On-site; AED 380,000 - 700,000; Full time

Job summary

Delivery Hero is seeking a Senior Data Scientist (AI & ML) to design, build, and deploy machine learning and generative AI systems powering product and business decisions. You will own a domain end-to-end, collaborating with product and business managers within a global AI hub.

The role covers problem framing, data modeling, feature engineering, model training, deployment, serving, and monitoring in production. You will mentor peers and advance MLOps practices.

Qualifications

• Bachelor's degree in CS/engineering or related field.
• 5+ years of experience across data science, ML engineering, and generative AI.
• Experience shipping ML models to production in online consumer products.
• Strong problem-solving and ownership mindset.
• Excellent collaborator and communicator.

Responsibilities

• Frame ambiguous business problems as clearly defined ML tasks with measurable success criteria.
• Provide high-quality data-driven insights and automated reporting to influence decisions.
• Design, build, and ship end-to-end ML and generative AI systems in production—data pipelines, feature engineering, model training, serving, and monitoring.
• Tackle engineering-heavy work end to end: robust ML systems, production-grade code, deployment, and maintenance.
• Train, evaluate, and iterate on models using appropriate algorithms to maximize business value.
• Leverage LLMs for data enrichment and automated decision-making within production systems.
• Maintain data models, features, and pipelines powering model training and performance measurement.
• Plan and analyze experiments (A/B and multivariate) to measure impact.
• Collaborate with product teams to translate opportunities into ML solutions.
• Mentor other data scientists and promote ML best practices.

Skills

Machine learning

Generative AI

Deep learning

NLP

Data mining

Model deployment

MLOps

SQL

Python

BigQuery

Education

Bachelor's degree in CS/engineering

Master's degree (preferred)

Tools

Scikit-learn

XGBoost

LightGBM

CatBoost

SVM

Keras

TensorFlow

PyTorch

Transformers

LLM fine-tuning

Airflow

BigQuery

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 Sr. Data Scientist (AI & ML) on the global AI hub , your mission will be to design, build, and ship the machine learning and generative AI systems that power decisions across product and business. You will own a particular domain end to end, working closely with product and business managers as part of a talented team of data scientists and machine learning engineers. You will own the full ML lifecycle, from problem framing, data modeling, and feature engineering through model training, deployment, serving, and monitoring in production. Many of our initiatives will focus on leveraging Generative AI and LLMs for tasks such as data enrichment, smart content understanding, and automated decision-making to enhance user experiences and business operations at scale.

Responsibilities

• Framing ambiguous business problems as well-defined machine learning and data science problems, with clear, objective success criteria.
• Providing high-quality, impactful insights and data-driven recommendations through rigorous analysis and automated reporting to drive strategic organizational choices.
• Designing, building, and shipping end-to-end machine learning and generative AI systems in production - spanning data pipelines, feature engineering, model training, serving, and monitoring.
• Taking on engineering-heavy work end to end: architecting robust ML-based systems, writing clean and scalable production code, and training, deploying, and maintaining reliable ML models that solve real business problems at scale.
• Training, evaluating, and iterating on models - selecting the simplest, most appropriate algorithms and architectures to deliver measurable business value.
• Leveraging LLMs and generative AI for data enrichment, smart content understanding, and automated decision-making within production systems.
• Building and maintaining the data models, features, and pipelines that power model training and allow us to measure performance and its drivers for your area of focus.
• Designing, planning, and analyzing experiments (A/B and multivariate tests) to rigorously measure model and product impact.
• Developing deep familiarity with source data and its generating systems through documentation, collaboration with engineering teams, and systematic data profiling.
• Partnering with product and business teams to identify high-impact opportunities and translate them into ML solutions and actionable, data-driven recommendations.
• Mentoring other data scientists in their growth journeys.
• Elevating engineering and ML best practices - improving our ways of working, tooling, MLOps, and internal training programs.

Technical Experience

• Deep expertise in machine learning, generative AI, deep learning, recommendation systems, NLP, pattern recognition, data mining.
• Deep hands-on knowledge of ML and GenAI frameworks (e.g. Scikit-learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Transformers, LLM fine-tuning).
• Strong software engineering fundamentals: excellent coding skills, a solid grasp of data structures and algorithms, and proven ability in both general system design and ML system design.
• Proven experience building, deploying, serving, and monitoring ML models in production, with a strong grasp of MLOps practices.
• Strong data and ML engineering skills, including building and orchestrating data and training pipelines (e.g. via Airflow) and robust feature engineering.
• Excellent SQL and competence with reproducible analysis and modeling in Python.
• Solid statistical foundations, including experiment design and analysis (A/B and multivariate) and inferential, causal, and predictive methods.
• Familiarity with data modeling and dimensional design.
• Strong command over the entire ML lifecycle, from problem formulation and data auditing through modeling, deployment, interpretation, and presentation.
• Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.).
• Experience with LLMs and NLP-based solutions for data enrichment and smart automation is a plus.
• Familiarity with BigQuery and the Google Cloud Platform 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 experience across data science, machine learning engineering, and generative AI, including shipping ML models to production.
• Experience building ML systems in an online consumer product setting is a plus.
• A good problem solver with a 'figure it out' growth mindset.
• An excellent collaborator.
• An excellent communicator.
• A strong sense of ownership and accountability.
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