Data Scientist

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

• BS/BA degree in a science related field (i.e, biological, chemical, data/computer science, engineering) with 5+ years of digital, data, and analytics experience in the healthcare, pharmaceutical, laboratory, or manufacturing industry.

OR

• MS or PhD degree in a science related field (i.e, biological, chemical, data/computer science, engineering) with 3+ years digital, data, and analytics experience in the healthcare, pharmaceutical, laboratory, or manufacturing industry.

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

• MS or Ph.D. in data/computer science or engineering, biological or chemical science or engineering or equivalent technical discipline. 
• In-depth experience with digital, data, and analytics techniques in the pharmaceutical industry. Specific experience or knowledge of biopharmaceutical manufacturing (upstream / downstream) is preferred.
• Experience with industrialization or implementation of models in a GMP environment, including development of model lifecycle management framework and integration into regulatory filings is preferred
• Familiarity and experience with relational databases, statistical softwares (i.e. SAS, SIMCA), modeling and visualization softwares (i.e. Python, R, Matlab, MS Power). Experience of developing or applying techniques such as pre-processing, classification, regression, clustering, dimensionality reduction and model selection.
• Experience with manufacturing / engineering environments including systems such as IP-21, M-ERP, LIMS, Aspen eBRs.
• Knowledge of GMPs and major regulatory agency regulations, specifically as they relate to data science or data validation.
• Strong interpersonal and leadership skills to manage a technical team and cross-functional teams. Prior experience managing a team or matrix team preferred.
• Strong verbal and written communication skills particularly in the area of technical and regulatory related matters. Able to present data science / statistical methods to non-statistical team members.
• Able to interact well with peers, subordinates, and senior personnel in scientific, quality, engineering and operational disciplines. Embraces a team-based culture.
• Demonstrates initiative to solve problems, effective at making and implementing decisions.