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Sr. Data Scientist (AI & ML)

Delivery Hero
Dubai, UAE
Full-time
Senior · 5+ years experience
Discovered 2 weeks ago
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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.
  • A 'keep it simple' approach to #makeithappen.
  • Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.
  • We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.
  • Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.

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