Machine Learning Engineer

We are looking for a talented Machine Learning Engineer with expertise in the supply chain domain to join our team and help optimize our operations through data-driven solutions.

• Develop and Deploy Machine Learning Models: Design, build, and deploy machine learning models to address challenges within the supply chain domain, including demand forecasting, inventory management, logistics optimization, and supplier performance evaluation.
• Data Analysis and Feature Engineering: Conduct extensive data analysis to extract insights, identify patterns, and engineer features that will improve model performance.
• Collaborate with Cross-Functional Teams: Work closely with supply chain analysts, data scientists, and software engineers to ensure seamless integration of ML models into existing systems.
• Optimize Supply Chain Processes: Utilize predictive analytics and machine learning techniques to enhance supply chain efficiency, reduce costs, and improve overall performance.
• Continuous Improvement: Monitor and refine machine learning models, ensuring they remain accurate and relevant as the business environment evolves.
• Documentation and Reporting: Maintain comprehensive documentation of models, processes, and workflows. Communicate findings and insights to stakeholders through clear and concise reports.

• Educational Background: Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning, or a related field.
• Experience: Proven experience (X+ years) in developing and deploying machine learning models, particularly within the supply chain domain.

• Proficiency in programming languages such as Python, R, or Java.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Strong understanding of supply chain concepts and challenges.
• Experience with data processing tools such as SQL, Hadoop, or Spark.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for model deployment.
• Problem-Solving Abilities: Strong analytical and problem-solving skills, with the ability to work with complex data sets and derive actionable insights.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.
• Team Player: Ability to work effectively in a collaborative, cross-functional team environment.