数据科学家（架构师）

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