Sr Advanced Chemical Engr

Job Description 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.