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