Data Scientist II - AI
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Key skills for this role
About the Role
Delivery Hero (talabat) seeks a Sr. AI Scientist to improve decision quality via data and machine learning, focusing on Generative AI for data enrichment and automation. You will own the data value chain and design ML/GenAI systems in production.
Key Skills for This Role
Responsibilities
- Leverage ambiguous business problems as opportunities to drive objective criteria using data
- Solve complex business problems using the simplest, most appropriate algorithms to deliver business value
- Design and implement effective and impactful machine learning and generative AI systems in production
- Develop deep understanding of product experiences and business processes in area of focus
- Develop deep familiarity with source data and its generating systems through documentation, interaction with engineering teams, and systematic data profiling
- Contribute to design and maintenance of data models to measure performance and comprehend performance drivers
- Work closely with product and business teams to identify important questions that can be answered effectively with data
- Deliver well formed, relevant, reliable, and actionable insights and recommendations through deep analysis and automated reports
- Design, plan, and analyze experiments (A/B and multivariate tests)
- Support product and business managers with KPI design and goal setting
- Mentor other data scientists in their growth journeys
- Contribute to improving ways of working, tooling, and internal training programs
Requirements
- Bachelor's degree in engineering, computer science, technology, or similar fields
- 3+ years of experience working in data science, machine learning, and Gen AI
- Experience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence
- Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine tuning)
- Excellent SQL
- Competence with reproducible data analysis using Python or R
- Familiarity with data modeling and dimensional design
- Strong command over the entire data lifecycle including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation
- Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques
- Familiarity with product data (impressions, events, etc.) and product health measurement (conversion, engagement, retention, etc.)
Full Job Posting
Company Description
- Since launching in Kuwait in 2004, talabat is the leading on demand food and Q commerce app for everyday deliveries, operating in eight countries across the region.
- We harness innovative technology and knowledge to simplify everyday life for customers, optimize operations for restaurants and local shops, and provide riders with reliable earning opportunities.
Job Description
- As a Sr. AI Scientist on the global AI hub, your mission is to improve the quality of decisions made across product and business via relevant, reliable, and actionable data.
- You will own a particular domain across product and business and work closely with product and business managers as part of a team of data scientists and data engineers.
- You will own the entire data value chain, including logging, data modeling, analysis, reporting, and experimentation.
- Many initiatives will focus on leveraging Generative AI for tasks such as data enrichment, smart content understanding, and automated decision making to enhance user experiences and business operations.
Responsibilities
- Leveraging ambiguous business problems as opportunities to drive objective criteria using data.
- Solving complex business problems using the simplest, most appropriate algorithms to deliver business value.
- Designing and implementing effective and impactful machine learning and generative AI systems in production.
- Developing a deep understanding of the product experiences and business processes that make up your area of focus.
- Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.
- Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.
- Working closely with product and business teams to identify important questions that can be answered effectively with data.
- Delivering well formed, relevant, reliable, and actionable insights and recommendations to support data driven decision making through deep analysis and automated reports.
- Designing, planning, and analyzing experiments (A/B and multivariate tests).
- Supporting product and business managers with KPI design and goal setting.
- Mentoring other data scientists in their growth journeys.
- Contributing to improving our ways of working, our tooling, and our internal training programs.
Technical Experience
- Experience in machine learning, generative AI, deep learning, recommendation systems, pattern recognition, data mining, and artificial intelligence.
- Deep knowledge and experience in ML and GenAI frameworks (e.g. Scikit learn, XGBoost, LightGBM, CatBoost, SVMs, Keras, TensorFlow, PyTorch, Hugging Face Transformers, LLM fine tuning).
- Excellent SQL.
- Competence with reproducible data analysis using Python or R.
- Familiarity with data modeling and dimensional design.
- Strong command over the entire data lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.
- Familiarity with different types of analysis, including descriptive, exploratory, inferential, causal, and predictive analysis.
- Deep understanding of various experiment design and analysis workflows and the corresponding statistical techniques.
- 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.
- Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.
Qualifications
- Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.
- 3+ years of experience working in data science, machine learning, and Gen AI.
- Experience doing data science in an online consumer product setting is a plus.
- A good problem solver with a ‘figure it out’ growth mindset.
- An excellent collaborator, and communicator.
- A strong sense of ownership and accountability.
- A ‘keep it simple’ approach to #makeithappen.
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