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oracle

Sr Advanced Data Scientist

Honeywell
Bengaluru, IND
Full-time
Senior · 6+ years experience
Hybrid
Discovered 3 weeks ago
azuredatabricksgeminihadoophivelangchain

Full Job Posting

Qualifications

  • YOU MUST HAVE
  • 6+ years of experience in data science, machine learning, or a related field.
  • Proven experience in developing and deploying AI models and algorithms.
  • Experience working with Databricks, Azure AI foundry, Google Gemini Enterprise Agent platform or similar for data preparation, training, and experiment tracking.
  • Strong programming skills in languages such as Python or R.
  • Strong project management and organizational abilities
  • Strong written and spoken communication skills in English.
  • WE VALUE
  • Bachelor’s or advanced degree in Computer Science, Data Science, Mathematics, or a related quantitative field.
  • Experience with big data platforms and distributed processing, including Hadoop, PySpark, Hive, and related technologies.
  • Strong foundation in machine learning and statistics, including feature engineering, algorithm selection, hyperparameter tuning, and predictive modeling.
  • Hands-on experience with GenAI and agentic frameworks, such as LangChain, LlamaIndex, vector indexes/databases, and S/4 AI agent workflows.
  • Experience preparing and analyzing multimodal data (text, images, audio, PDFs) and visualizing insights using modern data visualization tools.
  • Proven leadership and collaboration skills, including leading data science initiatives, solving complex problems, and working effectively in fast-paced, cross-functional teams

Responsibilities

  • KEY RESPONSIBILITIES
  • Collaborate with cross-functional teams to identify business challenges and opportunities for AI-driven solutions.
  • Translate business requirements into technical specifications for data science initiatives.
  • Partner with S4 team, functions and the business teams to understand AI capabilities, execute data readiness workstream for S4 and deploy AI enabled workflows for the PT business.
  • Evaluate model performance and fine-tune algorithms to improve accuracy and efficiency.
  • Deploy AI models with dependent solutions into production and monitor their performance to ensure reliability and scalability.
  • Design agentic AI architectures with prompt engineering and rule‐based automation to identify root causes, recommend actions, and continuously refine business‐aligned solutions.
  • Develop and implement advanced AI models and algorithms to analyze complex datasets.
  • Stay current with emerging AI research and technologies, incorporating relevant innovations into AI solutions.
  • Ensure AI solutions adhere to data governance standards and ethical best practices throughout their lifecycle.

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