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Honeywell

Diversified industrial conglomerate: aerospace, automation, safety

Senior Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • 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.

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.

Desired Qualifications

  • 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

About the Company

Honeywell

Diversified industrial conglomerate: aerospace, automation, safety

Honeywell operates in four main areas—aerospace, building automation, performance materials and technologies (PMT), and safety and productivity solutions (SPS). Its products couple hardware, software, and services, delivering integrated solutions for customers in design, manufacturing, installation, maintenance, and analytics. It stands out through a broad, diversified portfolio, a global presence, and the ability to connect multiple stages of the product lifecycle into one ecosystem. The company aims to help customers operate more reliably and efficiently, reduce costs and environmental impact, and grow recurring revenue by offering solutions, services, and digital platforms that link its hardware and software offerings.

Company size
10,001+
Company stage
IPO
Headquarters
Charlotte, NC
Founded
1906

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