
Model transformation Specialist
1 day ago
Role Overview:
We are looking for a skilled Model Transformation Specialist to join our team. The role focuses on transforming, monitoring, and maintaining model pipelines within a Big Data ecosystem. The ideal candidate will have strong expertise in Python/PySpark, solid SQL knowledge, and hands-on experience working with data pipelines. Exposure to model development or monitoring is essential, with a strong understanding of variables and model workflows.
Key Responsibilities:
- Design, develop, and maintain model transformation pipelines in Python/PySpark.
- Work with large datasets across distributed systems ( Big Data platforms ).
- Support model monitoring frameworks to ensure performance stability and compliance.
- Collaborate with data scientists and model developers to translate models into scalable, production-ready pipelines.
- Perform data extraction, transformation, validation, and analysis using SQL and PySpark.
- Ensure proper documentation of workflows, variables, and model processes.
- Contribute to process improvements in model lifecycle management.
Required Skills (Non-Negotiable):
- Strong hands-on programming in Python and PySpark .
- Solid knowledge of SQL and ability to work with Big Data technologies.
- Good understanding of model development landscapes (variables, features, and performance metrics).
Preferred Skills & Experience:
- Experience in model monitoring (performance checks, drift detection, stability tracking).
- Knowledge of end-to-end model pipelines (development to deployment).
- Familiarity with distributed systems (Hadoop, Spark, Databricks, or similar).
- Exposure to data governance, validation, and regulatory requirements in modeling.
Qualifications:
- Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- 3–6 years of experience in data engineering, model transformation, or model monitoring roles.
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