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Open nowFirst seen 16 hours ago

Data Scientist (Architect)

George Bernard Consulting185 open roles

Where
Colombo, Sri Lanka
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Your applicationOpen nowData Scientist (Architect)George Bernard Consulting · Colombo, Sri Lanka

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  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

11.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.3%7 days
  4. 17.6%14 days
  5. 34.3%30 days
  6. 43.5%60 days
This job: first seen 16 hours ago

The posting

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
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