Data Scientist
1 week ago
Your Mission This position is responsible for applying data-driven problem-solving, data science, and optimization techniques to resolve real-life manufacturing problems and deploy the ideated solutions in a production environment. What To Expect HMGICS is seeking data scientists with a deep interest in solving real-life industrial problems and applying their solutions at scale in a mass-production environment. Candidates should have a technological interest in at least one of the following domains: Data Analytics, Optimization, AI/ML, or Generative AI & LLMs. Additionally, candidates should have a functional interest in at least one of the following areas: logistics, supply chain, assembly, quality, maintenance, or enterprise functions. Participate as a data scientist in multi-disciplinary project teams aiming to improve the performance of our production environment in specific areas such as logistics and supply chain, assembly, maintenance, and quality. Perform explanatory analytics to understand the key underlying drivers of performance and how to further optimize them. Develop and maintain optimization or predictive models as required to assist production in delivering productivity, flexibility, quality, or sustainability improvements. Deploy these models in production and train engineers and technicians to leverage the insights for improving their day-to-day performance. What You'll Bring Bachelor's or Master's degree in Industrial Engineering, Computer Science, Mathematics, or equivalent practical experience. 2-5 years of project execution experience as a data scientist, resolving industrial problems across the value chain, including manufacturing, and ensuring the adoption of data science solutions. Preferred experience in the manufacturing and/or automotive industry. Strongly preferred experience in implementing data science and/or AI projects in real-life industrial environments (large POCs or at-scale deployments). Critical end-to-end problem-solving skills, including rapid and rigorous issue analysis, idea development and implementation, and feasibility demonstration and deployment at scale. Experience in applying Regression/Classification/Clustering models, Large scale data analysis, Time series analysis, Forecasting models, or Kernel-based methods. Experience in algorithm development using Mathematical programming (Linear programming, Mixed-integer programming), (Meta)Heuristic algorithms, Stochastic Process, or Combinatorial Optimization. Expertise in processing large-scale datasets in distributed data frameworks (Hadoop, Spark, or Hive). Expertise in data mining frameworks such as PyTorch, TensorFlow, Scikit-learn, or MLlib. Expertise in applying machine learning, Generative AI, LLMs is a plus. Fluent in English (written & spoken).
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