About this role
Job Description:
We are seeking a highly skilled and motivated Data Scientist to join our growing team . In this role, you will be responsible for designing, developing, and deploying machine learning models to optimize business operations. You will work closely with cross-functional teams to drive data-driven decision-making through accurate demand predictions, customer insights, and end-to-end machine learning model deployment .
Key Responsibilities:
- 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).
Qualifications:
- 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.