Description

You will own the end-to-end data science lifecycle, from exploratory data analysis to deploying machine learning models for enterprise-scale problems.

This role is on-site.

Responsibilities

• Perform exploratory data analysis and root cause analysis to identify key insights and anomalies in large-scale datasets.
• Develop and deploy machine learning models including classification, regression, clustering, and time-series forecasting.
• Design and execute statistical experiments, hypothesis testing, and rigorous validation frameworks.
• Optimize model performance and scalability using Python and SQL within enterprise environments.
• Collaborate with engineering teams to integrate ML solutions into production systems.

Required Skills

• 5+ years of hands-on experience in data science and machine learning.
• Proficiency in Python and SQL for data manipulation and analysis.
• Experience with ML libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Strong foundation in statistics, probability, and experimental design.
• Proven ability to work with large-scale enterprise datasets.
• Expertise in time-series forecasting and clustering techniques.

Preferred Skills

• Experience with deep learning frameworks like PyTorch or TensorFlow.
• Background in root cause analysis for complex system failures.

Key Skills

Education

Any Gradute