Job Description- Data Scientist
Process Data Scientist plays an important role within the process development team and the company by supporting process development and industrialization of new products, process optimization, investigations and problem solving, building predictive models, etc.
The right candidate will have a passion for discovering solutions hidden in data and working with stakeholders to develop, improve and industrialize product and processes.

Key Accountabilities:

• Partner with internal stakeholders from different teams to identify opportunity for applying data science to solve complex business challenges such as yield improvement, process robustness, proactive identification of potential issues.
• Support the team in design of experiments (DOE) using QbD approach, analyze and interpret the results and provide recommendations.
• Extract, transform and analyze data from multiple data sources ensuring data quality and integrity is maintained from source to the final output.
• Develop and implement algorithms and mathematical methods and models.
• Recommend and lead implementation of Process Analytical Technologies to enable data capture for use in quantitative analysis and improved level of process understanding.
• Provide clear and concise oral and written communication.
• Promote a strong quality mindset with a strong focus on data integrity, validation and data governance.

Education and Experience:

• MS or PhD in Process or Industrial Engineering
• Experience in statistical analysis, data science, process modeling or a similar technical field
• Minimum 1- 3 years of relevant industrial experience
• Experience with MVDA, DOE, SPC and statistics
• Strong experience in delivering insights through statistical data analysis, data modeling and data visualization
• Experience using tools such as SAS JMP, Python, Matlab, KNIME, and SIMCA
• Experience with developing business requirements, use cases and user stories in a data analytics context
• Exposure to best practices in data management and data governance practices
• Ability to deliver projects with complex requirements and a strong customer focus
• Ability to influence and communicate with a diverse group of stakeholders from multiple levels of management
• Ability to succeed in a team-oriented environment under very dynamic conditions
• Knowledge of Industrial Internet of Things