Data Scientist
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
[Data Analysis & Insights Generation]
- Analyze large, complex datasets to identify trends, patterns, and derive key underlying drivers of performance and how to further optimize them
- Identify opportunities for automation, process optimization, and innovation using data-driven approaches
[Data Science Solutions]
- Design, build, and deploy machine learning models and algorithms to solve business challenges and improve operational efficiency
- Collaborate with other team members to integrate AI/ML solutions into use case applications
- Train engineers and technicians to leverage the insights for improving their day-to-day performance
[Data Visualization & Reporting]
- Create interactive dashboards, reports, and visualizations to communicate insights to non-technical stakeholders.
- Use tools like Power BI, or Python libraries to present findings effectively
[Collaboration & Stakeholder Engagement]
- 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
- Act as a subject matter expert on data science, providing guidance and support to project teams
- Recommend and implement new tools, techniques, and methodologies to enhance project outcomes
What You'll Bring
- Bachelor's or Master's degree in Industrial Engineering, Computer Science, Statistics, 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 with data visualization tools like Tableau, Power BI
- 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.