11 Job Postings
2025-07-17 - 2026-07-17
The common responsibilities for this position include developing and deploying scalable AI/ML solutions for various business sectors, collaborating with business units to translate challenges into data requirements, and defining KPIs. Implementing robust data pipelines for cleaning, transformation, and feature engineering is essential, along with building and optimizing models for applications like predictive maintenance and demand forecasting. The role involves creating interactive dashboards to communicate insights, establishing Model Governance frameworks, and implementing CI/CD pipelines for model lifecycle management. Collaborating with data engineers and application developers to create end-to-end analytical pipelines is critical, as is clearly communicating complex AI methodologies to diverse audiences. Additionally, leading projects that integrate advanced AI into business processes, automating processes using data science, and designing AI and machine learning solutions for logistics challenges are key duties. The position also entails researching cutting-edge technologies in machine learning and natural language processing, developing AI models for a private GPT application, and ensuring best practices for model deployment and monitoring. Lastly, designing cloud-native AI solutions, maintaining comprehensive monitoring frameworks, and automating MLOps and model lifecycle management are integral responsibilities.
The percentages next to each skill reflect the sector’s demands in these respective skills. E.g., 30% means this skill has been listed in 30% of all the job postings in this sector.
The skills distribution tells you what specific skill sets are in demand. E.g., Skills with a distribution of “More than 50%” means that these skills are wanted in more than 50% of the job postings.
Job classifications that have advertised a position
Academic degree required as indicated by all job postings
Job subclassifications that have advertised a position