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Outline of TS/MS Data Scientist Role:
The TS/MS Data Scientist role will be responsible for identification and development of solutions using data science methods and principles to generate deeper insights from a greater variety of internal and external data sources. The TS/MS data Scientist will work closely with plant and lab TSMS functions to deliver automated data analysis and monitoring to increase efficiency, productivity, and process automation. The TS/MS data scientist will also provide support to the site statistical function.
Key Responsibilities:
1. Apply analytical and statistical methodology, including the concepts of Statistical Process Control (SPC), to process and experimental data to identify trends, assess process capability, and provide appropriate conclusions to enable data driven decision-making and to determine the root cause of process upsets.
2. Support of the real-time multivariate SPC programme using SIMCA-online.
3. Collaborate with laboratory and process scientists on the development of Raman spectroscopy based chemometric models
4. Use appropriate statistical methodologies to assign specifications, validation acceptance criteria, tech transfer criteria, material sampling criteria, comparability assessments and analysis of batch data for summary reports and product reviews.
5. Use of statistical and programming software (e.g. SAS, R, JMP, Python, SIMCA) to apply a broad range of data science and statistical applications, such as linear regression, DoE, multivariate analysis, and statistical modelling.
6. Assist with Design of Experiments (DoE) including data analysis to support lab studies and assist with the development of product control strategies
7. Interpret and communicate the results of data analytics and statistical analysis clearly and concisely to audiences with varying backgrounds and degrees of technical understanding.
8. Provide training and mentoring to technical staff to strengthen capabilities in statistical methods and data-based decision making.
9. Collaborate within cross-functional teams to integrate data analytics and statistical methodologies into everyday work, develop solutions, gain alignment, and deliver impactful business insights while engaging the necessary stakeholders to enable data driven decision-making.
10. Ensure data integrity by performing rigorous error checking, and data validation.
Pre-Requisites
11. A demonstrated interest in the field of statistics and data science
12. Skilled in quantitative analysis and data management
13. Strong problem solving skills
14. Demonstrated learning agility
15. Strong ability to influence
16. Ability to communicate effectively with all levels and functions in the organisation.
17. Ability to work on multiple concurrent project initiatives.
18. Ability to work in a team environment
19. Ability to build strong relationships across the organisation
20. Highly motivated
Educational/Experience Requirements
21. Third level qualification (eg. BSc or MSc) in Statistics, Data Science, Applied Mathematics or a relevant discipline.
22. Prior experience in a pharmaceutical manufacturing environment is preferable.
23. Prior knowledge and experience with programming, data analysis and process modelling in tools such as Python, R, Matlab, Unscrambler, SAS, SIMCA, Grams, JMP, etc. is preferable.
Additional Skills/Preferences:
24. Familiarity in areas like biochemistry, cellular biology, organic chemistry, physical chemistry, and cellular proliferation methods and techniques is desired.
25. Knowledge of pharmaceutical process steps such as biologics manufacturing, small molecule organic synthesis, and oral solid dosage form manufacturing is advantageous.
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.
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