Sr Advanced Chemical Engr

Key Responsibilities:

Operational Monitoring and Improvement:

• Monitor UOP technologies and identify areas for improvement and optimization, ensuring that assets receive the appropriate focus for enhancement.
• Review operations with customers and assist in defining and quantifying customer benefits, ensuring customer satisfaction and value from Honeywell's solutions.
• Troubleshoot issues and provide readily available technical solutions to customers, using data insights and proactive technical support.
• Conduct initial triage of technical issues, escalating them as needed to the technical support (TS) team.
• Use data mining techniques to handle unstructured data, identifying hidden patterns and relationships to derive technical insights.

Analytics and Reporting:

• Perform descriptive and inferential statistics on large datasets, summarizing trends and findings to inform decision-making.
• Apply predictive analytics and create models based on historical data to forecast future trends, improve solutions, and prevent future issues.
• Communicate insights from trends and diagnostic investigations to proactively resolve and prevent recurring problems.
• Work with the team to innovate new big data monitoring tools that utilize AI and machine learning to create advanced, exception-based analytics and dashboards for the GSC's efficient operation.

Solution Development & Continuous Improvement:

• Ensure upkeep of all solutions by troubleshooting PM/PTA/PRA/POA/Benchmarking/Future Solutions to ensure consistent availability and high operational uptime.
• Develop and optimize data pipelines that support product, system, and solution development.
• Drive the creation of innovative solutions for next-generation operational dashboards, with a strong focus on sustainability, efficiency, and scalability.

Cross-Functional Collaboration:

• Work with internal teams, including operations leaders, data scientists, and technical experts, to drive the success of Honeywell's 24/7 operations.
• Collaborate with external customers to ensure alignment with business objectives and key results for the GSCCC.
• Ensure the delivery of high-quality service, focusing on SMART data results while also identifying alternative solutions to overcome challenges with unstructured data.

Global Support & Communication:

• Ability to work in 24/7 shifts, providing continuous support and being flexible to come in for shift replacements on short notice.
• Support global customers, with potential internal/external travel (up to 10%) to troubleshoot issues and optimize solutions.
• Strong communication skills, both verbal and written, are essential for presenting technical solutions to customers, conveying data-driven insights, and engaging with stakeholders.

Qualifications:

Must Have:

• Bachelor's degree in Data Science, Computer Science, Engineering, or a related field.
• Strong analytical skills with the ability to interpret data, identify patterns, and make actionable recommendations.
• 4+ years of experience in data analytics, machine learning, AI-based solutions, or a similar technical role.
• Proficiency in data analytics tools and platforms such as Python, R, SQL, and data science frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
• Ability to handle and manipulate unstructured data and perform complex data mining tasks.
• Experience with big data platforms (e.g., Spark, Hadoop, Databricks) and working with large datasets.
• Problem-solving and troubleshooting skills, with the ability to define issues with limited information and generate solutions promptly.
• Experience working in a 24/7 operational environment, with a customer-focused approach to delivering timely support.

Nice to Have:

• Knowledge of UOP technologies and the ability to monitor and enhance operational processes.
• Familiarity with cloud computing platforms (e.g., Azure, AWS) and tools such as Informatica and NiFi for data flow automation.
• Experience with advanced analytics tools like ProSight for data visualization and technical insights.
• Familiarity with industrial automation, IoT, and refining/petrochemical sectors.
• Strong understanding of Data Science Open Source tools and technologies.