Description

You will build and manage data pipelines and predictive models to support sales forecasting and demand analysis.

This role is on-site.

Responsibilities

• Develop and implement machine learning algorithms including linear/logistic regression, decision trees, random forests, SVMs, and neural networks.
• Apply time-series analysis using ARIMA, SARIMA, and Prophet for sales data modeling.
• Execute statistical methods such as probability, hypothesis testing, regression, and clustering for data exploration.
• Process large-scale retail data using the Hadoop ecosystem.

Required Skills

• 5+ years of professional experience in data engineering or related roles.
• Proficiency in Python.
• Strong knowledge of SQL and NoSQL databases.
• Experience with Spark, Hive, MapReduce, and HDFS.
• Deep understanding of machine learning algorithms and statistical analysis.
• Expertise in time-series forecasting and modeling.
• Ability to apply statistical methods to complex datasets.

Preferred Skills

• Bachelor's degree in any field.

Key Skills

Education

Any Graduate