Description

Key Skills: Machine Learning, Forecasting, Data Scientist, Bayesian Statistics, Timeseries, Demand forecasting, Deep Learning, Analytics, Data Science, Tensorflow, Ms Sql

Roles and Responsibilities:

• Develop and evaluate time series forecasting models for demand forecasting using machine learning and deep learning approaches.
• Build probabilistic models using Bayesian statistics and Bayesian programming/modeling to quantify uncertainty in forecasts.
• Implement supervised and unsupervised machine learning workflows in Python, including feature engineering, model training, and validation.
• Use PyMC for Bayesian modeling and PyTorch/TensorFlow for deep learning model development.
• Design SQL-based data extraction and analytics workflows to support modeling, experimentation, and reporting.

Skills Required:

• 12 - 15 years of relevant experience in data science and forecasting.
• Machine learning (supervised & unsupervised) and strong data science fundamentals.
• Time series forecasting and forecasting model development for demand forecasting.
• Python and SQL for end-to-end modeling and analytics workflows.
• Scikit-learn, PyMC, PyTorch, and TensorFlow for model development and experimentation.

Good to Have:

• Experience with analytics-focused data science projects and MS SQL.

Education: Any Graduation or Any Post Graduation (Electrical, Electrical & Electronics, Communication & Networking, Computer Application, Computer Science, Industrial and Production Engineering)

Key Skills

Education

Any Graduate