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Job Description
- Develop and implement statistical and machine learning models to forecast product demand, sales, and inventory needs.
- Use time-series analysis, regression models, and other predictive modeling techniques to accurately predict demand trends.
- Design and implement customer segmentation models based on behavior, demographics, RFM analysis, and other relevant features.
- Analyze the effectiveness of segmentation strategies and adjust them based on customer behavior and evolving business needs.
- Build and maintain scalable ML pipelines to automate the deployment, monitoring, and retraining of models.
- Ensure the reliability and scalability of machine learning models by leveraging cloud infrastructure and containerization tools (e.g., Docker, Kubernetes).
- 5+ years of experience in a data science or machine learning role, with a focus on demand forecasting, segmentation, and model deployment.
- Proven experience with time series forecasting methods, statistical modeling, and machine learning algorithms.
- Strong hands-on experience with Python (or R) and libraries such as scikit-learn, pandas, numpy, statsmodels, and TensorFlow or PyTorch.
- Familiarity with MLOps frameworks and tools such as MLflow, Kubeflow, or similar platforms.
- Experience working with cloud platforms (AWS, GCP, Azure) and tools like Docker, Kubernetes, and CI/CD pipelines for deploying models.
- Experience in Supply Chain is a huge plus.
Skills
PythonRMachine LearningTensorFlowPyTorchScikit-learnPandasNumPyData SciencePredictive ModelingTime SeriesMLOpsAWSAzureGCPIf a job posting appears fraudulent, asks for payment, contains misleading information, or violates our guidelines, please report it immediately. Our team will review it promptly, Jobaaj does not charge any fee from the applicants.
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