Data Scientist (Architect)
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Summary
Senior data science architect who designs, builds, and deploys AI/ML models for complex business use cases — architecting solutions for unstructured data (text, images, logs, documents), building large-scale Python/PySpark/Scala data pipelines, driving the full ML lifecycle, creating BI dashboards, and mentoring data science teams.
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