Jobs → Data & Analytics → Data Scientist

About the Role We are looking for a Data Scientist to join our team in Dubai, UAE. This role involves working with Dataiku, Azure Databricks, and Python to develop and deploy machine learning models. Key Responsibilities • Design and implement machine learning models using Python, Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, and PyTorch • Utilize Dataiku for data preparation, feature engineering, model development, deployment, automation, and monitoring • Work with Azure Databricks, PySpark, MLflow, and large-scale distributed data processing • Develop and deploy Regression, Classification, Clustering, Forecasting, Recommendation, Customer Segmentation, Risk, and Fraud Detection models • Apply NLP, Text Analytics, Sentiment Analysis, and Generative AI techniques • Deploy and manage machine learning models in production using MLflow, Databricks Model Serving, and Azure ML • Implement MLOps practices including CI/CD pipelines, model versioning, experiment tracking, model registry, automated retraining, model monitoring, drift detection, performance optimization, and model governance Requirements • Strong programming expertise in Python, including Pandas, NumPy, Scikit-learn, XGBoost, TensorFlow, and PyTorch • Hands-on production experience with Dataiku for data preparation, feature engineering, model development, deployment, automation, and monitoring • Experience with Azure Databricks, PySpark, MLflow, and large-scale distributed data processing • Strong SQL skills with experience working on large-scale structured and unstructured datasets • Deep understanding of Machine Learning, Statistical Modeling, Predictive Analytics, Data Mining, Feature Engineering, Model Validation, Hyperparameter Optimization, and Model Explainability • Experience developing and deploying Regression, Classification, Clustering, Forecasting, Recommendation, Customer Segmentation, Risk, and Fraud Detection models • Hands-on experience in NLP, Text Analytics, Sentiment Analysis, Generative AI • Proven experience in deploying and managing machine learning models in production using MLflow, Databricks Model Serving, Azure ML • Experience with MLOps practices, including CI/CD pipelines, model versioning, experiment tracking, model registry, automated retraining, model monitoring, drift detection, performance optimization, and model governance