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Strong Tier-1 brand plus remote/hybrid increases applicant interest despite niche pharma MSAT specialization.
Role requires deep pharmaceutical MSAT and regulatory experience, limiting cross-industry transferability.
Explicit 10-16 years, advanced degree, and mandatory pharma/regulatory MSAT expertise make filters stringent.
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Lead data science initiatives for Global Supply Chain (GSC) focusing on new product introduction, root cause analysis, and batch quality assessments within product lifecycle management.
Drive adoption of rigorous data science methodologies across global sites, manage global networks, and influence policies to standardize data evaluation approaches.
Develop and mentor data science teams ensuring integration of data science and statistical methods into everyday MSAT processes and maintain external collaborations including regulatory engagement.
Master's or PhD in data science, computer science, statistics, mathematics, or related field.
10-16 years experience in pharmaceutical or biopharmaceutical MSAT with data science and/or programming, preferably pharmaceutical industry in multidisciplinary teams.
Strong programming skills in at least one scientific programming language (e.g., Python, R, GitHub).
Fluency in English; knowledge of additional languages like French, German, or Italian is desirable.
Experienced in managing complex data science projects aligned with regulatory requirements and product lifecycle management in a pharmaceutical setting.
Proficient at communicating complex data insights clearly to diverse stakeholders, including executives and regulatory authorities like FDA and EMA.
Skilled at leading cross-functional global teams and developing organizational data science capabilities to optimize manufacturing processes and product quality.