About
In this role, you will design, develop, and apply advanced data science, statistical, and machine learning methods to solve complex business problems. Embedded within customer engagements and fast-paced delivery teams, you will translate business challenges into scalable analytical and AI solutions that deliver measurable outcomes.
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Responsibilities
- Transform business challenges into data-driven solutions by identifying analytical opportunities, exploring data, engineering features, and developing predictive models.
- Design, develop, train, evaluate, and optimize machine learning models and statistical solutions for enterprise business scenarios.
- Apply techniques across exploratory data analysis, forecasting, classification, clustering, recommendation systems, anomaly detection, experimentation, causal analysis, and predictive analytics.
- Develop Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and Agentic AI frameworks.
- Integrate analytical and AI solutions into enterprise applications and business processes, ensuring scalability, robustness, and production readiness.
- Define evaluation metrics, validate model performance, monitor deployed models, and continuously improve solution accuracy and reliability.
- Work closely with customer teams to understand business processes, data landscapes, and operational challenges to co-create impactful AI solutions.
- Collaborate with AI Engineers, Data Engineers, Product Managers, and UX teams to deliver end-to-end AI products.
- Communicate analytical findings, technical trade-offs, and solution recommendations clearly to engineering teams and customer stakeholders.
- Stay current with the latest advancements in Data Science, Machine Learning, Generative AI, and Agentic AI, applying emerging techniques where appropriate.
Requirements
- Strong hands-on expertise in Data Science, Machine Learning, and Applied AI with excellent proficiency in Python and SQL.
- Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar technologies.
- Strong understanding of statistics, probability, hypothesis testing, experimental design, model evaluation, and feature engineering.
- Experience developing predictive models, recommendation systems, forecasting models, anomaly detection, and classification algorithms.
- Hands-on experience with Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
- Experience deploying machine learning and AI solutions using cloud-native platforms and modern MLOps practices.
- Familiarity with the company data landscapes including SAP S/4HANA, SAP HANA Cloud, SAP BW/4HANA, SAP Business Technology Platform (BTP), AI Core, AI Launchpad, and SAP AI services is an advantage.
- Ability to translate ambiguous business requirements into practical analytical solutions while balancing model accuracy, interpretability, scalability, and business value.
- Strong communication, collaboration, and problem-solving skills with the ability to work effectively in customer-facing environments.
Work Conditions
- Expected Travel: 0 - 10%
- Career Status: Professional
- Employment Type: Regular Full Time
- Additional Locations: #LI-Hybrid
Location
Dubai, Dubai, AE
