Senior Data Scientist

We are looking for a highly skilled Senior Data Scientist with strong expertise in PySpark, Machine Learning, and Big Data technologies to design, build, and deploy production-grade machine learning solutions . The ideal candidate will have hands-on experience working with cloud platforms and MLOps practices in real-world environments. Key Responsibilities Design, develop, and deploy scalable machine learning models for production use Work extensively with PySpark and Apache Spark for large-scale data processing Build and optimize end-to-end ML pipelines on cloud platforms Apply advanced statistical, machine learning, and deep learning techniques Develop and maintain production-grade ML systems Collaborate with data engineers, software engineers, and business stakeholders Implement MLOps/DevOps practices including CI/CD pipelines Monitor, evaluate, and improve model performance in production Required Skills Strong proficiency in Python & PySpark Solid understanding of Machine Learning & Statistics Hands-on experience with Apache Spark, Hadoop, Kafka Experience with Big Data platforms : AWS / Google Cloud / Azure / Oracle Cloud Expertise in ML techniques: Tree-based models (XGBoost, Random Forest, LightGBM) Deep Learning (CNNs, RNNs, GNNs, Transformers) Reinforcement Learning and Unsupervised Learning Experience in building production-ready ML models Knowledge of MLOps / DevOps tools : Docker, Kubernetes, CI/CD Familiarity with TensorFlow / PyTorch / Scikit-learn Qualifications Bachelors or Masters degree in a STEM discipline 4 to 6 years of experience as a Data Scientist or ML Engineer Proven track record of delivering ML solutions in production Preferred Skills (Good to Have) Experience with MLflow, Kubeflow Cloud certifications (AWS/GCP/Azure) Experience working in Agile/Scrum teams