Description

You will develop, maintain, and optimize machine learning forecasting models to improve accuracy and scalability.

This role is on-site.

Responsibilities

• Translate business requirements into scalable and maintainable ML solutions.
• Research and evaluate state-of-the-art ML and deep learning techniques for forecasting.
• Build end-to-end ML workflows including feature engineering, training, validation, and deployment.
• Monitor model performance and implement strategies for drift detection and retraining.

Required Skills

• 5–8 years of experience in Data Science or 3+ years developing forecasting solutions.
• Expertise in Python, Spark, and SQL.
• Strong knowledge of forecasting techniques: ARIMA, SARIMA, Prophet.
• Proficiency with ML frameworks: GLM, GBDT, XGBoost, Seq2Seq, Transformers, LSTM/GRU.
• Hands-on experience with end-to-end ML development from preparation to productionization.
• Experience with ML platforms/tools: MLflow, Kubeflow, Databricks.
• Strong background in Big Data tools: Spark, Hadoop ecosystem, Airflow.
• Familiarity with Git, Bitbucket, CI/CD, and version control practices.

Key Skills

Education

Bachelor's degree