Data Scientist

Responsibilities

• Design, develop, and deploy Machine Learning and Generative AI models for real-world applications
• Perform data preprocessing, feature engineering, and model optimization on large-scale datasets
• Implement and optimize ML pipelines for training and inference using AWS services like SageMaker, Lambda, and S3
• Develop end-to-end ML solutions including model versioning, monitoring, and retraining
• Collaborate with data engineers and software developers to integrate models into production systems
• Perform exploratory data analysis (EDA) and statistical analysis to drive decision-making
• Write efficient SQL queries for data extraction and transformation

Requirements

• 3 to 5 years of experience in Data Science
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, or Scikit-Learn
• Hands-on experience with Generative AI models (GPT, LLMs, etc.)
• Experience deploying ML models on AWS (SageMaker, Lambda, S3, EC2)
• Strong knowledge of SQL for managing large datasets
• Understanding of MLOps principles and CI/CD pipelines for ML

Preferred Qualifications

• Experience with Google Cloud AI or Azure ML
• Knowledge of APIs, microservices, and containerization (Docker, Kubernetes)
• Experience with deep learning architectures like CNNs, RNNs, or Transformers
• Familiarity with big data technologies like Spark or Hadoop

About the Company

Quation is a data analytics consultancy that empowers brands to unlock the true potential of their data. We translate complex data landscapes into actionable insights through AI, ML applications, marketing analytics, and pricing optimization across various industries including retail, manufacturing, and finance.