Sr Advanced Data Scientist

Posted 6 Days Ago
Be an Early Applicant
4 Locations
Hybrid
Senior level
Aerospace • Security • Energy • Industrial
The Role
Lead design, development, deployment, and monitoring of advanced AI/ML models and agentic solutions. Collaborate with cross-functional teams, translate business needs into technical specifications, ensure data readiness for S4, apply prompt engineering and automation, and uphold data governance and ethical standards.
Summary Generated by Built In
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. 
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 

About UsHoneywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

Skills Required

  • 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.
  • 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 and working effectively in fast-paced, cross-functional teams.

Honeywell Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Honeywell and has not been reviewed or approved by Honeywell.

  • Retirement Support Retirement plans feature a notably strong company 401(k) match with vesting after three years, enhancing long-term savings security. Additional tax-advantaged accounts and company contributions for eligible earners further strengthen financial preparedness.
  • Leave & Time Off Breadth Time off policies include flexible or unlimited vacation for many salaried roles and a broad observed-holiday schedule, providing manager-approved flexibility. This structure supports rest and work-life balance across varied needs.
  • Parental & Family Support Parental leave offers paid time for birth, adoption, or foster care that can be taken consecutively or intermittently. The design enables practical flexibility in how family leave is used.

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The Company
HQ: Charlotte, NC
110,269 Employees
Year Founded: 1906

What We Do

Honeywell is a Fortune 500 company that invents and manufactures technologies to address tough challenges linked to global macrotrends such as safety, security, and energy. With approximately 110,000 employees worldwide, including more than 19,000 engineers and scientists, we have an unrelenting focus on quality, delivery, value, and technology in everything we make and do.

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