Data Driven Forecasting Expert

2 days ago

Bengaluru, Karnataka, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Senior Data Scientist / ML Engineer

We are modernizing our demand forecasting capabilities through an advanced machine learning platform. A leading organization is seeking a highly skilled Senior Data Scientist / Machine Learning Engineer to design and operationalize cutting-edge forecasting solutions at scale.

This role combines hands-on machine learning with solid software engineering practices to deliver robust, scalable, and transparent forecasting capabilities.

  • Create production-grade forecasting models using industry-leading methodologies.
  • Develop end-to-end machine learning pipelines for data ingestion, feature engineering, model training, and deployment.
  • Design probabilistic models to quantify forecast uncertainty.
  • Write clean, modular, object-oriented code following best practices.
  • Implement MLOps best practices including model versioning, monitoring, and CI/CD.
  • Work with distributed training frameworks for scalable model development.
  • Collaborate with cross-functional teams (engineering, product, strategy) to align solutions with business objectives.
  • Work with cloud-based environments (e.g., Databricks, AWS, GCP) for large-scale data processing.

Demand forecasting or retail/supply chain management experience is essential. Familiarity with containerization (Docker, Kubernetes), data orchestration frameworks (Airflow, Prefect), and explainable AI frameworks is also required.

Required experience includes 3–6 years of relevant experience in Data Science / ML Engineering, strong proficiency in Python and core libraries such as pandas, numpy, scikit-learn, and hands-on experience with deep learning frameworks (preferably PyTorch).

Other requirements include experience with distributed training and large-scale datasets, proven ability to build scalable, production-grade ML pipelines, familiarity with MLOps practices (CI/CD, monitoring, retraining pipelines), solid understanding of statistical modeling, regression, and time series analysis, and excellent problem-solving, communication, and collaboration skills.

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