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لوگوی اسنپ شاپ | SnappShop
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Senior Data Scientist

اسنپ شاپ | SnappShop·تهران·۳ هفته پیش

حضوریارشدقراردادیتوافقی

اسنپ شاپ | SnappShop

شرح موقعیت

Duties Model Development: Design, build, train, and rigorously test machine learning models (including classical ML and deep learning) to solve specific business challenges. End-to-End Implementation: Execute all steps of the machine learning pipeline, from initial data exploration and feature engineering through to final model deployment. Productionization: Work with engineering teams to successfully productionize models, ensuring they are scalable, reliable, and perform efficiently in real-time environments. Validation and Optimization: Plan and execute rigorous A/B testing and other validation experiments to measure model performance and impact. Deep Learning Application: Apply and implement solutions using modern deep learning frameworks, with a strong preference for PyTorch. Technical Analysis: Apply advanced knowledge of statistics and machine learning theory to choose appropriate algorithms, interpret results, and ensure sound experimental design. Performance Monitoring: Continuously monitor the performance of deployed models, diagnose issues, and implement necessary retraining and improvements. Preferred Competencies

نیازمندی‌ها

  • 5+ years of professional experience in a Data Scientist or Machine Learning Engineer role with a primary focus on model development.
  • Demonstrated experience managing the end-to-end machine learning lifecycle in a production setting.
  • Proven ability to productionize models and validate their business impact using controlled experiments like A/B testing.
  • Expertise with deep learning frameworks, particularly PyTorch.
  • Strong knowledge of machine learning algorithms, principles, and best practices.
  • Solid foundation in statistics, including hypothesis testing, experimental design, and data interpretation.
  • Strong experience with Python and excellent proficiency in SQL for data extraction and manipulation.
  • Experience utilizing MLFlow or similar MLOps tools for experiment tracking, model registry, and managing the ML workflow.
  • Familiarity with Natural Language Processing (NLP) techniques and models is desired.