Digital Capabilities Associate
Sesto Fiorentino, Tuscany
At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
- Support the overall manufacturing organization finding new valuable and actionable process insights by modelling, transforming and analysing large data sets from different manufacturing system sources.
- Develop and deploy advanced analytics solution aimed at supporting decision making, monitoring & optimize process outcomes.
- Contribute to scout, assess and deploy innovative methods and technologies that allow to expand the available manufacturing data and enable to access new valuable information.
- Contribute to deploy the data driven culture within the manufacturing organization.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases to drive optimization and improvement initiatives
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Develop custom data models and algorithms to apply to data sets and perform output quality assessment and test
- Use predictive modeling to increase business outcomes.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Manage the solutions developed during their whole life cycle
- Coach the manufacturing organization on data analytics methods and technologies.
- All manufacturing functions
- Global IDS functions
- University Degree in Computer Science, Engineering or other scientific disciplines
- Fluent English spoken and written
- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
- Understanding of the Manufacturing S95 Information System Architecture
Eli Lilly and Company, Lilly USA, LLC and our wholly owned subsidiaries (collectively “Lilly”) are committed to help individuals with disabilities to participate in the workforce and ensure equal opportunity to compete for jobs. If you require an accommodation to submit a resume for positions at Lilly, please email Lilly Human Resources ( Lilly_Recruiting_Compliance@lists.lilly.com ) for further assistance. Please note This email address is intended for use only to request an accommodation as part of the application process. Any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
To submit resume, visit https://www.lilly.com/careers and apply to Req ID R-1399.
Lilly is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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