Data Scientist (Architect)

Job Description Lead the design, development, and deployment of AI/ML models for complex business use cases. Architect solutions involving unstructured data, including text, images, logs, and documents. Build large-scale data pipelines using Python, PySpark, or Scala. Drive machine learning lifecycle processes: data preparation, feature engineering, model selection, training, validation, and monitoring. Create BI dashboards and data visualizations to communicate insights to leadership and stakeholders. Work closely with engineering teams to operationalize models in production environments. Provide technical leadership and mentorship to data science teams. Ensure solutions are scalable, secure, and aligned with enterprise data architecture standards. Explore new techniques, tools, and frameworks to enhance analytics capabilities Requirements Minimum 10+ years of total IT experience. Minimum 5+ years of hands-on expertise in the following (must-have): AI/ML algorithm development , Unstructured data processing , Python with PySpark or Scala , Machine Learning engineering , BI Reporting / Dashboard Development Strong background in data modeling, statistical analysis, and MLOps concepts. Experience architecting end-to-end data science solutions at enterprise scale. Nice-to-Have Skills Experience with Azure cloud services (Azure ML, Data Factory, Databricks, Synapse, etc.). Knowledge of big data platforms and distributed computing. Understanding of NLP, deep learning, or advanced analytics techniques. Exposure to CI/CD, model versioning, and automated ML pipelines Originally posted on Himalayas