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About the role
As a Senior Data Scientist at our company, you will be responsible for the following key tasks: - Develop and implement machine learning models and algorithms. - Work closely with project stakeholders to understand requirements and translate them into deliverables. - Utilize statistical and machine learning techniques to analyze and interpret complex data sets. - Stay updated with the latest advancements in AI/ML technologies and methodologies. - Collaborate with cross-functional teams to support various AI/ML initiatives. Qualifications required for this role include: - Bachelors degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. - Strong understanding of machine learning, deep learning, and Generative AI concepts. Preferred Skills: - Experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, Computer vision(yolo), Deep Learning stack, NLP using python. - Strong knowledge and experience in Generative AI/ LLM based development. - Strong experience working with key LLM models APIs (e.g. AWS Bedrock OR Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain OR LlamaIndex OR RAG). - Experience with cloud infrastructure for AI/Generative AI/ML on AWS, Azure. - Expertise in building enterprise-grade, secure data ingestion pipelines (ETL Gluejob, Quicksight) for unstructured data including indexing, search, and advanced retrieval patterns. - Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. - Proficiency in generating and working with text embeddings with an understanding of embedding spaces and their applications in semantic search and information retrieval. - Experience with RAG concepts and fundamentals (VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. - Knowledge of training and fine-tuning Foundation Models (Athropic, Claud, Mistral, etc.), including multimodal inputs and outputs. - Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and frameworks. (e.g., pandas, NumPy, scikit-learn), Glue crawler, ETL. - Experience with data visualization tools (e.g., Matplotlib, Seaborn, Quicksight). - Knowledge of deep learning frameworks (e.g., TensorFlow, Keras, PyTorch). - Experience with version control systems (e.g., Git, CodeCommit). Good to have Skills: - Knowledge and Experience in building knowledge graphs in production. - Understanding of multi-agent systems and their applications in complex problem-solving scenarios. Please note that Pentair is an Equal Opportunity Employer. With our expanding global presence, cross-cultural insight and competence are essential for our ongoing success. We believe that a diverse workforce contributes different perspectives and creative ideas that enable us to continue to improve every day. As a Senior Data Scientist at our company, you will be responsible for the following key tasks: - Develop and implement machine learning models and algorithms. - Work closely with project stakeholders to understand requirements and translate them into deliverables. - Utilize statistical and machine learning techniques to analyze and interpret complex data sets. - Stay updated with the latest advancements in AI/ML technologies and methodologies. - Collaborate with cross-functional teams to support various AI/ML initiatives. Qualifications required for this role include: - Bachelors degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. - Strong understanding of machine learning, deep learning, and Generative AI concepts. Preferred Skills: - Experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, Computer vision(yolo), Deep Learning stack, NLP using python. - Strong knowledge and experience in Generative AI/ LLM based development. - Strong experience working with key LLM models APIs (e.g. AWS Bedrock OR Azure Open AI/ OpenAI) and LLM Frameworks (e.g. LangChain OR LlamaIndex OR RAG). - Experience with cloud infrastructure for AI/Generative AI/ML on AWS, Azure. - Expertise in building enterprise-grade, secure data ingestion pipelines (ETL Gluejob, Quicksight) for unstructured data including indexing, search, and advanced retrieval patterns. - Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. - Proficiency in generating and working with text embeddings with an understanding of embedding spaces and their applications in semantic search and information retrieval. - Experience with RAG concepts and fundamentals (VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. - Knowledge of training and fine-tuning Foundation Models (Athropic, Claud, Mistral, etc.), including multimodal inputs
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