Key Responsibilities

Design, develop, and maintain scalable data pipelines for data collection, processing, and analysis.
Build, train, validate, and deploy Machine Learning and AI models into production environments.
Collaborate with data scientists, business stakeholders, and engineering teams to understand business requirements and translate them into technical solutions.
Develop feature engineering frameworks and model training workflows.
Implement ML Ops practices for model deployment, monitoring, versioning, and retraining.
Optimize ML models for performance, scalability, and reliability.
Work with structured and unstructured datasets from various sources.
Develop and maintain ETL/ELT processes and data integration solutions.
Create dashboards, reports, and visualizations to support business insights.
Ensure data quality, governance, security, and compliance standards are met.
Evaluate emerging AI, ML, and data technologies and recommend best practices.

Data Science Engineer

Job Description