Data Scientist

The purpose of the Data Scientist role is to embed data-driven approaches into the core of our R&D processes, build a data-centric culture, provide recommendations on the process to adopt on linking R&D generated data to the rest of the business. The Data Scientist is expected to perform all duties in a safe manner and to maintain a safe and secure operating environment.

• Data Collection and Management:
• Design and implement robust data collection frameworks within the existing capabilities, ensuring data is accurate, consistent, and relevant.
• Collaborate with R&D team to adapt R&D processes and data workflow, ensuring data is accessible, secure, and compliant with regulations.
• Data Analysis and Insights Generation:
• Perform advanced statistical analysis, predictive modeling, and machine learning to uncover trends, patterns, and insights from R&D data.
• Develop custom algorithms and models to support product development, process optimization, and innovation initiatives.
• Tool and Technology Integration:
• Evaluate and implement data analytics tools and technologies to enhance the R&D digitalization process.
• Work with IT and engineering teams to integrate these tools with existing systems and workflows.
• Visualization and Communication of Findings:
• Create clear and compelling data visualizations to communicate complex analytical results to non-technical stakeholders.
• Present findings and recommendations to R&D leadership and cross-functional teams, driving informed decision-making.
• Collaboration and Cross-Functional Support:
• Partner with researchers, marketing, and product development teams to provide data-driven support throughout the R&D lifecycle.
• Contribute to cross-functional projects, offering expertise in data science and analytics.
• Innovation and Continuous Improvement:
• Stay up-to-date with the latest advancements in data science, AI, and machine learning, incorporating new techniques and methodologies into R&D processes.
• Continuously improve data analytics practices, seeking ways to optimize and streamline data-driven decision-making.
• Mentorship and Training:
• Provide guidance and training to R&D team members on data science principles, tools, and best practices.
• Foster a data-centric culture within the department, encouraging the adoption of data-driven approaches.
• Project Management:
• Lead data science projects from conception through execution, managing timelines, resources, and deliverables.
• Compliance and Ethical Considerations:
• Ensure all data science practices adhere to ethical guidelines, privacy regulations, and company policies.
• Work in collaboration with IT to address and mitigate risks associated with data security and the use of AI in R&D processes.
• Other:
• Other duties assigned to safely perform.
• Proven track record of collaborating in diverse teams.