Remote Chemical Process Analyst

About the Role

Our client is seeking a skilled Remote Chemical Process Analyst to support their analytical needs from anywhere within the country. This position involves the in-depth analysis of process data to identify trends, optimize performance, and troubleshoot issues without direct physical site presence. You will work closely with plant engineers and management teams, providing critical insights derived from data. This is an excellent opportunity for an analytical engineer who thrives on data interpretation and remote collaboration, contributing to the efficiency and effectiveness of our chemical operations nationwide.

Key Responsibilities

• Collect, analyze, and interpret complex process data from various chemical manufacturing sites.
• Identify performance bottlenecks, inefficiencies, and potential safety hazards through data analysis.
• Develop reports and presentations summarizing findings and recommending process improvements.
• Collaborate with plant engineers and operators to implement data-driven solutions and monitor their impact.
• Utilize statistical software and data visualization tools to communicate insights effectively.
• Contribute to the development and refinement of data collection and analysis methodologies.

Requirements

• Bachelor's degree in Chemical Engineering , Data Science, or a related quantitative field.
• 3-5 years of experience in data analysis, process monitoring, or chemical engineering support roles.
• Proficiency in data analysis software (e.g., Excel, Python with libraries like Pandas, R) and statistical methods.
• Strong understanding of chemical processes and manufacturing principles.
• Excellent analytical, problem-solving, and critical thinking skills.
• Effective communication skills for remote collaboration and reporting.

Benefits

• Competitive salary and performance-based incentives.
• Comprehensive health and wellness benefits.
• Flexible remote work arrangement with a focus on work-life balance.
• Opportunities for professional development in data analytics and chemical engineering .
• Direct impact on improving operational efficiency across multiple sites.