Honeywell Aerospace

Sr Advanced Data Scientist

Posted 7 Days Ago

Be an Early Applicant

3 Locations

Hybrid

Senior level

Aerospace

The Role

Lead development and deployment of advanced AI models, design agentic architectures and prompt engineering, collaborate with cross-functional teams, ensure data readiness and governance, monitor model performance, and integrate AI workflows into production for business impact.

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 cross-functional teams.