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Mid-level popular role, metro location, and broad ML/pharma skills increase candidate competition.
High because role mandates pharma life-sciences data experience and client-facing consulting background.
High due to explicit 5.5+ years, 2 years pharma leadership, and mandatory ML, GenAI, and cloud deployment skills.
Own end-to-end data science engagements in pharma commercial analytics, from problem definition to ML solution delivery and operationalization.
Lead and mentor a team of data scientists, overseeing technical decisions, model quality, and project delivery across multiple engagements.
Drive client relationships, provide thought leadership, and contribute to practice growth via business development and capability building.
5.5+ years of hands-on data science and ML experience with at least 2 years in leadership roles within pharma consulting or client-facing settings.
Bachelor's or Master's degree in engineering, statistics, mathematics, or relevant quantitative field.
Experience with life sciences data types such as claims (Komodo, IQVIA, Symphony), specialty pharmacy, CRM, DDD, Lab, HCP, account or patient-level data.
Strong proficiency in Statistics, ML (supervised, unsupervised, deep learning, GenAI), Python, SQL, and cloud/distributed platforms (Databricks, PySpark, AWS/Azure).
Experienced in pharma commercial analytics with ability to translate business problems into data science solutions and manage client communications effectively.
Proven leadership in managing data science teams, ensuring quality and delivery across multiple concurrent projects.
Capable of driving growth in a consulting practice through technical expertise, client engagement, and business development activities.