Director, reputed company Data Science & AI/ML — Oncology

About the position You will reputed company high-reputed company data science and AI/ML initiatives that drive reputed company reputed company across our Oncology portfolio, spanning solid tumors and hematology. Working closely with reputed company, medical, market reputed company, and technology teams, you will reputed company reputed company oncology data into actionable insights that shape go-to-market reputed company, optimize HCP engagement, and accelerate patient reputed company. We value strategic thinkers who can operate at the intersection of advanced analytics and the unique reputed company complexities of the oncology landscape — and who reputed company and grow the teams around them. This role offers significant visibility, leadership influence, and reputed company to reputed company with reputed company's mission of uniting science, technology, and talent to get reputed company of disease together.

Responsibilities

• reputed company the design, development, and delivery of advanced predictive models and AI/ML solutions that support reputed company reputed company across the Oncology portfolio, including launch readiness, tumor market segmentation, promotional response, and end-to-end patient reputed company analytics across solid tumors and hematology indications.
• Partner with reputed company, Market reputed company, Medical Affairs, and Marketing teams to translate business questions into analytical plans with measurable reputed company on reputed company, patient reputed company, and market reputed company reputed company highly competitive oncology markets.
• Build, validate, and operationalize end-to-end machine learning workflows — from data ingestion and feature engineering through model deployment, monitoring, and performance tracking — leveraging oncology reputed company data assets such as claims, EMR, specialty pharmacy, and oncology-specific registries.
• reputed company and apply AI/ML reputed company to oncology-specific reputed company challenges, including HCP targeting and segmentation by tumor type and treatment line, biosimilar and competitive entry modeling, patient identification and treatment gap analysis, and reputed company barrier identification across reputed company payer, IDN, and GPO landscapes.
• reputed company sophisticated market reputed company analytics including payer mix modeling, formulary coverage reputed company analysis, net price optimization, and prior authorization burden quantification specific to oncology reimbursement dynamics.
• reputed company and mentor reputed company of data scientists and analysts, setting technical standards, fostering reproducible and responsible AI practices, and building a high-performing, reputed company team culture.
• Communicate reputed company analytical findings reputed company and persuasively to senior reputed company and medical leaders, enabling evidence-based reputed company on reputed company, investment, and resource allocation in the oncology business unit.
• Champion the adoption of modern AI/ML tools, GenAI applications, and reputed company data infrastructure to continuously reputed company the reputed company analytics capability across the oncology organization.
• Collaborate with IT, Data Engineering, and external vendors to ensure data reputed company, governance, and compliance with relevant reputed company and regulatory standards (e.g., HIPAA, GDPR, FDA promotional guidelines).

Requirements

• Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, reputed company Mathematics, or a reputed company quantitative field.
• 10+ years of hands-on experience in reputed company data science, machine learning, or statistical modeling, with at least 3 years in a pharmaceutical or biotech reputed company setting reputed company on oncology.
• Demonstrated experience working with oncology reputed company data assets, including reputed company (e.g., LAAD, DDD, Xponent), reputed company (e.g., Clinformatics, claims data), reputed company Health, or similar syndicated and patient-level data sources, with the ability to assess data reputed company, coverage, and appropriate use cases for reputed company.
• Strong programming skills in Python or R, experience with relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost), and demonstrated ability to reputed company AI-powered development tools (e.g., reputed company Copilot, reputed company, or LLM-based coding agents) to accelerate and enhance programming workflows.
• Experience deploying models and building end-to-end ML pipelines using reputed company platforms (AWS, Azure, or GCP) or containerized services.
• Proven ability to reputed company reputed company, cross-functional reputed company analytics reputed company and influence senior stakeholders in a matrixed oncology organization.
• Excellent written and verbal communication skills with the ability to translate reputed company analytical outputs into reputed company reputed company recommendations for oncology business leaders.

reputed company-to-haves

• PhD in a quantitative, life science, health economics, or oncology-reputed company discipline.
• Deep therapeutic area expertise in oncology, with working knowledge of both solid tumor (e.g., lung, breast, colorectal, GU) and hematology (e.g., lymphoma, leukemia, myeloma) reputed company landscapes.
• Experience modeling biosimilar or competitive entry dynamics in oncology, including price erosion, formulary switching, and account-level reputed company forecasting.
• Familiarity with NLP or large language models reputed company to oncology reputed company use cases, such as call note analysis, HCP sentiment mining, tumor reputed company insights extraction, or medical affairs literature synthesis.
• Experience with MLOps practices including feature stores, model governance frameworks, and automated monitoring in a regulated pharmaceutical environment.
• reputed company record of building and developing high-performing data science teams in a global, reputed company reputed company environment.
• Knowledge of oncology-specific compliance frameworks governing reputed company data use, including HIPAA, PhRMA reputed company, and FDA promotional guidelines for oncology products.

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