AI/ML Data Scientist

• Develop and Implement AI/ML Models for predictive analytics, automation, and intelligent decision-making.
• Analyze Large Datasets using statistical and machine learning techniques to extract valuable insights.
• Optimize and Scale ML Pipelines for real-time and batch processing in production environments.
• Deploy AI Models on Cloud Platforms such as AWS, GCP, or Azure using MLOps practices.
• Collaborate with Data Engineers to ensure seamless integration of AI/ML models into enterprise data platforms.
• Design and Optimize Feature Engineering techniques to enhance model performance.
• Implement Explainable AI (XAI) Practices to ensure model transparency and fairness.
• Ensure Data Quality and Integrity through rigorous data validation and preprocessing steps.
• Utilize Open-Source ML Libraries and Frameworks , including TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Develop and Maintain AI/ML Pipelines using tools such as Apache Airflow, MLflow, and Kubeflow.
• Research and Innovate new AI/ML methodologies to improve business processes and automation.
• Monitor Model Performance and Drift , ensuring continuous optimization and re-training.
• Support Data Science Initiatives by mentoring junior data scientists and collaborating with cross-functional teams.

• 10+ years of experience in data science, machine learning, and AI model development.
• Strong Expertise in Machine Learning Algorithms , including supervised, unsupervised, and reinforcement learning.
• Proficiency in Programming Languages such as Python, SQL.
• Hands-on Experience with ML Frameworks , Open Source libraries such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Experience with Cloud AI Services , such as AWS SageMaker, and platforms such as Data bricks, Snowflakes.
• Deep Knowledge of MLOps Practices , including CI/CD for ML, model versioning, and monitoring.
• Strong Understanding of Data Technologies , including Spark and distributed computing.
• Experience in Natural Language Processing (NLP), CNN , and Deep Learning Techniques.
• Familiarity with AI Ethics, Bias Mitigation, and Explainable AI (XAI).
• Knowledge of Databases and SQL for data retrieval and preprocessing.
• Strong Analytical and Problem-Solving Skills to derive insights and optimize AI/ML solutions.

• Bachelors or Master s degree in Data Science, AI, Machine Learning, or a related field.
• Experience with Generative AI, LLMs (Large Language Models), and Transformer Architectures.
• Familiarity with Kubernetes, Docker, and containerized ML deployments.
• Exposure to Graph Neural Networks, Time Series Forecasting, and Edge AI.
• Certification in AWS, Google, or Azure AI/ML platforms.

Disclaimer: The job location mentioned in this description is based on publicly available information or company headquarters. Candidates are advised to verify the exact job location directly with the employer before applying.