Description

You will develop, maintain, and optimize Machine Learning forecasting models to improve accuracy and scalability.

Responsibilities

• Develop, maintain, and optimize Machine Learning forecasting models.
• Translate business requirements into scalable and maintainable ML solutions with data science, data engineering, and business teams.
• Research and evaluate state-of-the-art ML and deep learning techniques for forecasting and optimization.
• Build end-to-end ML workflows: feature engineering, training, validation, deployment, and monitoring.
• 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.

Preferred Skills

• Experience with hierarchical models (Top-Down, Bottom-Up).
• Familiarity with ML monitoring and model performance evaluation tools.

Key Skills

Education

Bachelor's degree