Job Description

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.
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.