Advanced Data Scientist

Honeywell•Hamilton Township, NJ

22d•Hybrid

About The Position

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. 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.

Requirements

Advanced analytics, artificial intelligence, and machine learning technologies expertise
Significant Salesforce platform experience, including Salesforce Agentforce, Einstein AI, Data Cloud, and CRM Analytics
Experience building intelligent agents, predictive analytics models, conversational AI experiences, customer insight capabilities, and scalable machine learning solutions
Experience with generative AI solutions using large language models, retrieval-augmented generation, and enterprise AI architectures
Experience designing data pipelines and feature engineering processes utilizing Salesforce Data Cloud and enterprise data platforms
Experience developing conversational AI experiences and autonomous agent workflows integrated with the Salesforce ecosystem
Experience evaluating emerging AI and Salesforce technologies
Experience establishing model governance, monitoring, explainability, security, and responsible AI practices
Experience collaborating with software engineers, product managers, architects, and business stakeholders
Ability to translate complex analytical findings into clear, actionable recommendations
Mentoring developers and contributing to technical standards and reusable best practices

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.