Lead Data Scientist

Join a team recognized for leadership, innovation, and diversity.

As the Lead Data Scientist supporting Commercial Excellence at Honeywell Aerospace, you will help shape how advanced analytics, machine learning and agentic AI transform commercial decision making across the entire commercial and pricing functions.

Reporting to the Senior Manager, Commercial Lab - Advanced Analytics & AI, you will work at the intersection of business strategy and emerging technology, partnering directly with commercial leaders to identify high value opportunities and turn complex business challenges into intelligent, scalable solutions driving real business outcomes.

You will lead the hands-on development of predictive models, optimization algorithms, AI agents, and decision support tools - from early experimentation through supporting production deployment. This role offers the opportunity to influence commercial strategy, drive measurable financial outcomes, and help establish next generation AI capabilities across Honeywell Aerospace.

You will also provide technical leadership and mentorship to Data Scientists and Data Analysts, helping build advanced analytics capabilities within the Commercial Analytics Lab.

You Must Have

• 5+ years of experience in data science, machine learning, advanced analytics, decision science, or applied AI
• Strong proficiency in Python and experience developing and deploying machine learning models
• Experience working with cloud data platforms such as Databricks, Google Cloud Platform, Snowflake, or Microsoft Fabric
• Demonstrated ability to translate ambiguous business challenges into analytical approaches and practical, scalable solutions
• Experience collaborating directly with business stakeholders to define requirements, communicate insights and deliver measurable business value

US PERSON REQUIREMENTS

Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

We Value

• Experience developing AI agents, LLM powered applications, RAG solutions, or multi agent workflows using frameworks such as LangGraph, LangChain or similar technologies
• Experience applying machine learning and AI to real world business challenges in pricing, sales, or commercial operations
• Strong business acumen, intellectual curiosity, and ability to connect advanced technologies with tangible business outcomes
• Experience rapidly prototyping and iterating on AI solutions in collaborative, cross functional environment
• Ability to communicate complex technical concepts in clear, actionable terms to business leaders and executive stakeholders

Additional

• Hybrid Work Schedule Note: For the first 90 days, new hires must be prepared to work 100% onsite Monday-Friday. Following 90 days, the team is expected to be in the office at least 3 days per week and can be remote 2 days.
• Travel: Up to 10%
• Reports To: Senior Manager, Commercial Lab - Advanced Analytics & AI
• Location(s): Phoenix, AZ (preferred), or Charlotte, NC

Join a company that''s reintroducing itself to the aviation community we''ve helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we''re launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.

Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world''s aircraft, your work here has reach that''s rare to find anywhere else.

Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we''re shaping what comes next.

Every horizon. Every mission. Every day.

Benefits:

Beyond a performance-driven salary, you''ll work alongside dedicated experts on technology that''s advancing aviation. As a Honeywell Aerospace employee, you''re eligible for a comprehensive benefits package that includes:

• Employer-subsidized medical, dental, vision and life insurance
• Short-term and long-term disability coverage
• 401(k) match, flexible spending accounts and health savings accounts
• Employee assistance program and educational assistance
• Parental leave and 12 paid holidays
• Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/

POSTING TIMELINE

The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.

Honeywell Aerospace products and services are found on aircraft across commercial aviation, defense and space. We operate through three business areas:

Electronic Solutions develops the avionics, navigation systems, sensors and electromagnetic defense technology on board 90% of the world''s aircraft Engines & Power Systems provides the propulsion, auxiliary power and electrical systems that keep those aircraft flying Control Systems supplies the thermal and motion control systems that support takeoff, landing and the safety of everyone on board

With approximately 58,000 employees worldwide and net sales of $17.4B in 2025, we are also advancing systems for autonomous and supersonic platforms - bringing the same focus on safety and efficiency to the next era of flight. Explore our businesses: https://www.honeywellaerospace.com

#Li-Hybrid

Advanced Analytics & Machine Learning Leadership

• Lead the development of advanced analytics, machine learning, and optimization models supporting commercial decision-making.
• Design and deploy predictive and prescriptive models across pricing, sales performance, forecasting, marketing analytics, and commercial strategy.
• Translate complex business problems into scalable analytics solutions and decision frameworks.
• Guide model development best practices including feature engineering, model validation, experimentation, and performance monitoring.

Generative AI & Agentic Solution Development

• Design, develop and deploy AI agents and agentic workflows that automate complex commercial processes and enable intelligent decision making
• Build solutions leveraging large language models (LLMs), retrieval augmented generation (RAG), and orchestration frameworks to connect AI with enterprise data and business systems
• Develop AI commercial assistants and autonomous or supervised workflows supporting pricing, sales, proposals and commercial operations
• Partner with business and technology teams to prototype, evaluate and operationalize AI solutions with appropriate guardrails, monitoring and oversight

Commercial Decision Science & Business Impact

• Partner directly with commercial and pricing leaders to identify business challenges, assess opportunities and translate business needs into high impact analytics and AI solutions
• Develop AI decision support tools that improve pricing effectiveness, sales productivity, sales outcomes and commercial planning and strategy
• Build predictive models and ML classifiers supporting uses cases such as price optimization, demand forecasting, win rate prediction and opportunity prioritization
• Translate complex analytical findings into clear business recommendations, actionable insights, and measurable outcomes

Mentorship & Technical Leadership

• Provide technical mentorship and guidance to an Advanced Data Scientist, supporting their development in machine learning, experimentation, and decision science methods.
• Promote best practices in model development, experimentation design, and analytics reproducibility.
• Foster collaboration between data scientists, analytics engineers, and commercial stakeholders.
• Help build scalable data science capabilities within the commercial analytics organization.

Advanced Analytics & Machine Learning Leadership

• Lead the development of advanced analytics, machine learning, and optimization models supporting commercial decision-making.
• Design and deploy predictive and prescriptive models across pricing, sales performance, forecasting, marketing analytics, and commercial strategy.
• Translate complex business problems into scalable analytics solutions and decision frameworks.
• Guide model development best practices including feature engineering, model validation, experimentation, and performance monitoring.

Generative AI & Agentic Solution Development

• Design, develop and deploy AI agents and agentic workflows that automate complex commercial processes and enable intelligent decision making
• Build solutions leveraging large language models (LLMs), retrieval augmented generation (RAG), and orchestration frameworks to connect AI with enterprise data and business systems
• Develop AI commercial assistants and autonomous or supervised workflows supporting pricing, sales, proposals and commercial operations
• Partner with business and technology teams to prototype, evaluate and operationalize AI solutions with appropriate guardrails, monitoring and oversight

Commercial Decision Science & Business Impact

• Partner directly with commercial and pricing leaders to identify business challenges, assess opportunities and translate business needs into high impact analytics and AI solutions
• Develop AI decision support tools that improve pricing effectiveness, sales productivity, sales outcomes and commercial planning and strategy
• Build predictive models and ML classifiers supporting uses cases such as price optimization, demand forecasting, win rate prediction and opportunity prioritization
• Translate complex analytical findings into clear business recommendations, actionable insights, and measurable outcomes

Mentorship & Technical Leadership

• Provide technical mentorship and guidance to an Advanced Data Scientist, supporting their development in machine learning, experimentation, and decision science methods.
• Promote best practices in model development, experimentation design, and analytics reproducibility.
• Foster collaboration between data scientists, analytics engineers, and commercial stakeholders.
• Help build scalable data science capabilities within the commercial analytics organization.