Data Scientist II

As a Data Scientist II here at Honeywell, you will leverage your expertise in audit analytics, data engineering, risk and fraud analytics, predictive modeling, and advanced AI technologies to drive impactful data science initiatives aligned with regulatory compliance and business objectives.You will report directly to the Director of IT and Cybersecurity Audit and you’ll work out of our Charlotte HQ on a Full-Time / Hybrid work schedule.In this role, you will impact the development and deployment of advanced analytics and machine learning models that support audit, risk management, cybersecurity and fraud detection efforts, while ensuring compliance with industry regulations and enhancing operational efficiency.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.YOU MUST HAVE5+ years of experience in data science, audit analytics, risk analytics, fraud analytics, or a related field.3+ years of experience developing and implementing predictive or machine learning models, including classification, regression, anomaly detection, or risk scoring.3+ years of experience developing data pipelines, ETL processes, business intelligence /data visualization or data warehouse solutions using technologies such as PowerBI, Snowflake, Databricks, or Spark.3+ years of experience applying data analytics to Enterprise Risk Management, business, risk, audit, compliance, cybersecurity, or fraud-related problems.WE VALUEIntrapreneurial growth mindset—demonstrated ability to proactively identify opportunities, challenge existing approaches, experiment responsibly, learn from feedback, and take ownership of innovative solutions that create measurable business value.Experience managing projects and communicating with senior stakeholders.Strong analytical skills with the ability to translate complex data into actionable insights.Ability to collaborate effectively across technical and business teams in a fast-paced environment.Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or a related field.Experience applying analytics to audit, risk management, cybersecurity, fraud detection, or regulatory compliance use cases.Experience with audit analytics aligned to frameworks such as SOX, GDPR, NIST, or PCI DSS.Proficiency in programming languages such as Python and SQL.Experience with explainable AI techniques such as SHAP or LIME.Experience monitoring model performance, detecting model drift, and retraining machine learning models.Experience implementing CI/CD pipelines for analytics or machine learning workflows.Experience with generative AI, agentic AI, large language models (LLMs), natural language processing (NLP), or AI-enabled data summarization.Experience using security and cybersecurity tools such as Splunk, Microsoft Defender, SentinelOne, Tanium or Qualys.Experience with cloud platforms and machine learning lifecycle management.BENEFITS OF WORKING FOR HONEYWELLIn 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 ( 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. Job posted 9/14/2026ABOUT HONEYWELL TECHNOLOGIESHoneywell 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 ( ResponsibilitiesLead audit analytics initiatives aligned with SOX, GDPR, NIST, and PCI DSS frameworks, including scoping, probabilistic modeling, testing, and reporting.Design, develop, and maintain robust ETL pipelines and data warehouses using Snowflake and Databricks.Design, develop, and maintain enterprise risk and fraud analytics models focusing on KRIs, risk scoring, anomaly detection, and fraud prevention while leveraging data visualization tools, such as PowerBI.Build and optimize predictive models for classification and regression tasks.Utilize SHAP and LIME techniques to interpret and explain model predictions.Monitor model performance, detect drift, and retrain models as necessary to maintain accuracy.Leverage Spark for large-scale data processing and analytics.Implement CI/CD pipelines for analytics and machine learning workflows to ensure seamless deployment and integration.Utilize security tools such as Splunk, Defender, SentinelOne, and Qualys to support data security and compliance.Apply generative and agentic AI technologies for audit use cases, integrating platforms like ServiceNow, Azure AI, large language models (LLMs), and natural language processing (NLP) for data summarization and insights.Full timePosting Date: 2026-09-27