Data Scientist

ResponsibilitiesWork with large and complex data sets to solve challenging business problemsCollect, clean, and preprocess large datasets for analysis & model trainingPerform exploratory data analysis (EDA) to uncover insights and inform model developmentDevelop, train, and optimize machine learning models using state-of-the-art algorithms and frameworksBuild end-to-end ML pipelines, including data ingestion, transformation, model training, validation, and deploymentAutomate workflows for model training, testing, and deployment using CI/CD pipelines and MLOps toolsCollaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutionsQualification5+ years of experience in data science, machine learning, or AIExpertise 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 for data queryingAbility to build data pipelines (Spark, Airflow, Hadoop) and work with big data toolsUnderstanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps)Experience deploying models on AWS, Google Cloud, Azure, or similar (e.g., Sagemaker, Vertex AI)Educational qualifications: Bachelor’s degree in Computer Science, Engineering, or related field required