✨ AI Summary
Virtusa Middle East FZ-LLC is seeking a Data Scientist in Dubai, UAE. The role involves designing and developing scalable machine learning models and AI-driven solutions to solve complex business challenges. Key responsibilities include collecting, cleaning, and preprocessing large datasets, performing exploratory data analysis, developing and optimizing machine learning models, building end-to-end ML pipelines, and automating workflows using CI/CD and MLOps tools. The Data Scientist will collaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutions.
Candidates should have 5-7 years of experience in data science, machine learning, or AI, with expertise in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs). Strong proficiency in Python and/or R, familiarity with SQL, and experience with data pipeline tools (Spark, Airflow, Hadoop) are required. Experience in model serving, API development (FastAPI, Flask), Docker, Kubernetes, CI/CD pipelines, MLOps tools (MLflow/Kubeflow), and cloud platforms (AWS, Google Cloud, Azure) is also necessary. Educational qualifications include a Master's degree in Computer Science or a related field, or a Master's in Statistics with a Bachelor's in Statistics.
Designs and develops scalable machine learning models and AI-drivensolutions to address complex business challenges and enhance decision-making processesKEY RESPONSIBILITIE SWork with large and complex data sets to solve challenging businessproblemsCollect, clean, and preprocess large datasets for analysis & model trainingPerform exploratory data analysis (EDA) to uncover insights and inform modeldevelopmentDevelop, train, and optimize machine learning models using state-of-the-artalgorithms and
Requirements
5 years of experience in data science, machine learning, or AI
vision, or generative AI (e.g., LLMs).
Strong proficiency in Python and/or R; familiarity with SQL for data querying
Ability to build data pipelines (Spark, Airflow, Hadoop) and work with big data
tools
optimizing model performance for real-time or batch inference.
MLflow/Kubeflow for model lifecycle management (MLOps)
Classified: Internal\ FAB.
Internal
Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g.,
Sagemaker, Vertex AI)
Work Experience
5-7Years
Description
Designs and develops scalable machine learning models and AI-drivensolutions to address complex business challenges and enhance decision-making processesKEY RESPONSIBILITIE SWork with large and complex data sets to solve challenging businessproblemsCollect, clean, and preprocess large datasets for analysis & model trainingPerform exploratory data analysis (EDA) to uncover insights and inform modeldevelopmentDevelop, train, and optimize machine learning models using state-of-the-artalgorithms and frameworksBuild end-to-end ML pipelines, including data ingestion, transformation, modeltraining, validation, and deploymentAutomate workflows for model training, testing, and deployment usingCI/CD pipelines and MLOps toolsCollaborate with cross-functional teams to integrate models into applicationsand deliver end-to-end solutions