Description

You will design, build, and deploy forecasting and predictive analytics models using statistical and deep learning techniques.

This role is on-site.

Responsibilities

• Develop time series and forecasting models using Bayesian statistics and traditional statistical approaches.
• Build and evaluate deep learning models, specifically CNN-based architectures, for predictive analytics.
• Perform data analysis and feature engineering to enhance model performance and reliability.
• Design end-to-end ML workflows covering experimentation, validation, and model monitoring.
• Support scalable data and ML pipelines in Databricks environments and query MySQL data.

Required Skills

• 8-12 years of experience in data science and predictive modeling.
• Strong expertise in Bayesian statistics and statistical modeling for forecasting.
• Proven track record with time series analysis, model evaluation, and iteration.
• Proficiency in Python and deep learning frameworks (CNNs).
• Experience integrating models with MySQL-backed data sources.
• Ability to deliver end-to-end analytics solutions.

Preferred Skills

• Hands-on experience with MLOps practices and AI/ML delivery.
• Practical exposure to Databricks for scalable data engineering.

Key Skills

Education

Any Graduate