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Tier‑1 employer and metro location increase applicant density, but senior pharmaceutical MSAT specialization limits broad competition.
High - deep pharmaceutical MSAT, regulatory and manufacturing expertise limits cross‑industry transferability.
High - explicit 10–16 years, pharmaceutical MSAT domain expertise, advanced degree and regulatory experience required.
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Lead data science initiatives within Global Supply Chain to drive process understanding, product and process optimization, and data-driven problem solving across global sites.
Own end-to-end data science model lifecycle including design, development, validation, monitoring, and communication of insights aligned to regulatory and business standards.
Build and lead a high-performing team, mentor others, influence internal policy and external regulatory discussions, and standardize data science methodologies globally.
Masters or PhD in data science, computer science, statistics, mathematics, or related field.
10-16 years of experience applying data science, preferably in pharmaceutical or biopharmaceutical MSAT within multidisciplinary multicultural teams.
Strong programming skills in at least one scientific programming language (Python, R, GitHub) and expertise in pharmaceutical industry data science applications.
Fluency in English; hybrid work location in India; occasional international travel required.
Experienced leader capable of managing matrix teams and developing data science capabilities in a regulated pharmaceutical environment.
Skilled communicator able to translate complex data insights for diverse organizational levels including executives and regulators.
Strategic thinker with proven ability to influence policy, standardize methodologies globally, and engage with regulatory authorities and industry forums.