AI-Fueled Demand Planning Specialist

5 days ago

Guntur, Andhra Pradesh, India beBeeData Full time US$ 1,40,000 - US$ 1,70,000
Supply Chain Planning Expertise Required

We are revolutionizing the supply chain management industry with our AI-driven demand planning and inventory replenishment software.

Our total addressable market (TAM) for supply chain management (SCM) software is substantial and growing rapidly.

We target the rapidly growing segment of the supply chain management (SCM) industry: small and medium-sized businesses (SMBs).

Job Requirements
  • Design, build, and deploy production-grade forecasting models
  • Develop end-to-end machine learning pipelines for data ingestion, feature engineering, model training, and deployment
  • Build 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 to align solutions with business needs

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

Key Responsibilities
  1. Develop a comprehensive understanding of supply chain management principles and techniques
  2. Design and implement advanced forecasting models using machine learning algorithms
  3. Work with large-scale datasets to develop predictive analytics solutions
  4. Collaborate with cross-functional teams to ensure seamless integration of ML solutions
  5. Stay up-to-date with the latest advancements in ML and deep learning
Requirements
  • 3–6 years of relevant experience in Data Science / ML Engineering
  • Strong proficiency in Python and core libraries such as pandas, numpy, scikit-learn
  • Hands-on experience with deep learning frameworks (preferably PyTorch)
  • 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

You will work with cloud-based environments (e.g., Databricks, AWS, GCP) for large-scale data processing.

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