The Role

We are seeking a Senior Data Scientist to lead the design, development, and deployment of Artificial Intelligence (AI), Generative AI, Agentic AI, and advanced analytics solutions that accelerate digital transformation across Manufacturing, Quality, Supply Chain, Engineering, R&D, andCorporatefunctions.

What You’ll Do

AI Solution Development

• Design, develop, and deploy enterprise AI solutions using Large Language Models (LLMs), Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) architectures.

• Build AI assistants, intelligent agents, chatbots, and copilot solutions that automate engineering, manufacturing, quality, supply chain, and business workflows.

• Develop natural-language-to-SQL solutions that allow users to interact with enterprise data using conversational interfaces.

• Design semantic search, document intelligence, and knowledge management solutions to improve access to organizational knowledge.

• Evaluate emerging AI technologies and lead pilot projects to demonstrate business value.

Analytics & Tool Development

• Develop analytical tools and automation platforms using Python, SAS, SQL, and cloud-native technologies.

• Apply machine learning, statistical analysis, predictive modeling, forecasting, and optimization techniques to solve complex business problems.

• Create scalable AI and analytics applications that can be deployed across multiple business units.

• Design and implement APIs, web applications, and self-service analytical platforms.

• Develop reusable frameworks and accelerators that improve development speedand solutionscalability.

Data Engineering & Data Architecture

• Design, develop, and maintain analytical data models, views, and datasets within Snowflake, Google Cloud Platform (GCP),BigQuery, and enterprise data platforms.

• Collaborate with IT and Data Engineering teams to establish scalable data architectures supporting AI and analytics initiatives.

• Investigate and resolve data quality, data integration, and data pipeline issues affecting business-critical analytics.

• Support enterprise data governance and data quality programs.

Business Partnership

• Partner with Manufacturing, Quality, R&D, Supply Chain, Operations, andCorporateteams to identify high-value automation and AI opportunities.

• Translate business requirements into technical AI and analytical solutions.

• Present technical concepts, solution roadmaps, and business value to leadership and stakeholders.

• Serve as a technical advisor for AI, advanced analytics, and workflow automation initiatives.

What We Seek

• Master's degree in Data Science, Computer Science, Electrical Engineering, Statistics, Artificial Intelligence, Machine Learning, or a related technical field.

• 5+ years of experience developing data science, machine learning, AI, or analytics solutions.

• Strong expertise in Python and SQL development.

• Hands-on experience with Generative AI, LLMs, Agentic AI, and RAGarchitectures.

• Experience developing enterprise AI applications using frameworks such asLangChain, Hugging Face, Vertex AI, OpenAI, Gemini, or similar technologies.

• Experience deploying production AI solutions on cloud platforms such as GCP, AWS, or Azure.

• Strong understanding of machine learning, NLP, predictive modeling, statistical analysis, and optimization techniques.

• Experience developing REST APIs and scalable software applications.

• Experience working with cloud data platforms such as Snowflake,BigQuery, Databricks, or similar technologies.

• Knowledge ofMLOps,LLMOps, CI/CD pipelines, and modern AI deployment practices.

• Experience with Power BI, Tableau, or modern visualization platforms.

• Ability to collaborate effectively with both technical and business teams.

• Excellent communication, presentation, and stakeholder management skills.

Preferred Qualifications

• Experience developing multi-agent AI frameworks and autonomous workflow solutions.

• Experience withFastAPI, cloud-native application development, and AI platform engineering.

• Experience implementing semantic search, vector databases, embeddings, and knowledge retrieval systems.

• Experience supporting manufacturing, engineering, quality, or supply chain organizations.