Drive and execute projects within Advanced Process Innovation program (i.e., primarily within process efficiency workstream) by developing analytical models and/or machine learning algorithms. This role is designed as a developer role within agile project management method, with potential opportunity to be product owner.
Collaborate with internal production, technology and engineering teams, and potential external partners to deliver Advanced Process Innovation program and identify additional opportunities for improvements to fill the program pipeline.
Communicate results, findings and recommendations from analysis clearly to relevant stakeholders through clear and concise reports and presentations.
Collaborate with Data Engineer to design MLOps/DevOps pipeline, maintain data pipelines and databases, ensuring data integrity, while keeping in compliance within organization data governance and security policies.
Act as a coach for the organization to democratize machine learning techniques by running initiatives to support this objective.
Stay abreast with industry trends and emerging technology in data science and machine learning methodology with the intent to bring them into the organization.
REQUIREMENTS
Master or Ph.D. in Data Science, Business Informatics, Computer Science, Chemical Engineering or a related field.
Minimum of 5 years of experience in the field of data science/analytics, DevOps/MLOps, data engineering and project management (full-stack ML engineering). Experience within chemical or manufacturing industry is preferred.
Proficiency in programming languages such as Python & R, collaborative tools like GitHub & Azure DevOps, and experience with data visualization tools (i.e., Tableau, PowerBI).
Excellent communication skills, intercultural competence and team spirit with curiosity to explore new technologies and tools in the industry
Basic knowledge of process and/or chemical engineering is desirable.
Familiarity with other engineering/process control related software (ASPEN, PACE, etc) is a plus.
Network with local universities and local vendors/suppliers is a plus
