About The Role

As an Advanced Data Scientist here at Honeywell, you will leverage advanced analytics, artificial intelligence, and machine learning technologies to transform customer engagement, service operations, and sales processes across the enterprise. This role combines deep data science expertise with significant Salesforce platform experience, including Salesforce Agentforce, Einstein AI, Data Cloud, and CRM Analytics.

You will partner with business leaders, product teams, digital transformation organizations, and Salesforce platform teams to design and deploy AI-powered solutions that drive measurable business outcomes. Your work will focus on building intelligent agents, predictive analytics models, conversational AI experiences, customer insight capabilities, and scalable machine learning solutions that enhance operational efficiency and customer experiences.

You will report directly to our Director of R&D, and you will work out of our Hamilton, NJ location on a 3-day in office hybrid work schedule.

KEY RESPONSIBILITIES

Design, develop, and deploy advanced machine learning and AI solutions that address complex business challenges.
Lead the development of intelligent agent solutions leveraging Salesforce Agentforce and Einstein AI capabilities.
Build predictive models for customer behavior, lead scoring, opportunity forecasting, churn prediction, and service optimization.
Partner with CRM, sales, service, and marketing teams to define AI use cases, success criteria, and measurement frameworks.
Develop and operationalize generative AI solutions using large language models, retrieval-augmented generation, and enterprise AI architectures.
Design data pipelines and feature engineering processes utilizing Salesforce Data Cloud and enterprise data platforms.
Develop conversational AI experiences and autonomous agent workflows integrated with the Salesforce ecosystem.
Evaluate emerging AI and Salesforce technologies and recommend enterprise adoption strategies.
Establish model governance, monitoring, explainability, security, and responsible AI practices.
Collaborate with software engineers, product managers, architects, and business stakeholders to deliver production-ready solutions.
Translate complex analytical findings into clear, actionable recommendations for business and executive stakeholders.
Mentor developers and contribute to technical standards and reusable best practices across the organization.

YOU MUST HAVE

Bachelor's degree from an accredited institution in Computer Science, Data Science, Statistics,
Mathematics, Engineering, Information Systems, or a related quantitative field.
5+ years of experience in data science, machine learning, artificial intelligence, or advanced analytics roles.
3+ years of hands-on experience with Salesforce platform technologies.
Proven experience designing, implementing, or deploying Salesforce Agentforce solutions.
Strong experience with Salesforce Einstein AI, Data Cloud, Service Cloud, and Sales Cloud.
Experience developing machine learning models using Python and modern machine learning frameworks.
Strong knowledge of statistical modeling, predictive analytics, experimentation, and model evaluation methodologies.
Experience working with structured and unstructured enterprise data at scale.
Strong communication, collaboration, and stakeholder management skills.

WE VALUE

Master's degree or PhD in a quantitative discipline.
Salesforce Agentforce Specialist, Salesforce AI Specialist, or related Salesforce certifications.
Expertise with generative AI, large language models, prompt engineering, and enterprise AI applications.
Experience implementing AI-powered customer service or digital sales transformation initiatives.
Knowledge of cloud platforms such as Microsoft Azure, Amazon Web Services, or Google Cloud Platform.
Experience with MLOps, model deployment, observability, monitoring, and lifecycle management.
Familiarity with vector databases, semantic search, and retrieval architectures.
Experience working in large enterprise environments with complex data and integration ecosystems.
Strong business acumen and the ability to connect AI investments to measurable business outcomes.
Agile Development methodologies.

BENEFITS OF WORKING FOR HONEYWELL

In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. Learn more

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. Posting Date: August 31, 2026

ABOUT HONEYWELL TECHNOLOGIES

Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world’s most mission-critical challenges, enhancing the quality of life for people and communities around the world. We serve the building, industrial, and process sectors with a broad portfolio of services, solutions, and products, underpinned by our Honeywell Technologies Accelerator operating system and Honeywell Technologies Forge intelligence layer. By combining the deep domain expertise of our more than 50,000 employees with decades of data from our global installed base, we are uniquely positioned to lead the industrial sector’s transition from automation to autonomy. Learn more

THE BUSINESS UNIT

Honeywell’s Advanced Process Control Software and Outcome-Based Solutions and Enterprise Performance Management business unit delivers innovative software solutions that optimize industrial processes and enhance operational efficiency. Our technologies enable customers to achieve superior process control, reduce variability, and improve overall plant performance through data-driven insights and advanced automation capabilities.