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Director, Development Analytics Strategy (Convergence Catalyst)

Posted on Apr 5, 2021 by Pharmacyclics

Libertyville, IL 60048
Research
Immediate Start
Annual Salary
Full-Time


The Director will coordinate the execution of the (Clinical) Development Analytics strategy and vision by working with the functional area leadership and cross-functional stakeholders. Help define Convergence data integration strategies and advance Clinical Development priorities while maintaining alignment with the overarching R&D Convergence data integration framework and priorities.



  • Act as a key member of the R&D Convergence (Data Integration) Core team responsible for defining and executing the R&D Convergence strategy, and represent Clinical Development in cross-functional R&D discussions and decision-making forums related to Convergence data integration.

  • Collaborate with scientists, clinicians, and data scientists within Clinical Development and across R&D to identify and lead projects involving the aggregation and analysis of large data sets to identify key trends and insights that advance scientific understanding.

  • Ensure that projects create a substantial return on investment and a meaningful impact on advancement of the AbbVie pipeline of new medicines and/key functional/therapeutic area or R&D priorities.


Responsibilities:



  • Coordinate the execution of the (Clinical) Development Analytics strategy and vision by working with the functional area leadership and cross-functional stakeholders

  • Drive the communication and change management across Development functions by highlighting the Development Analytics roadmap, progress, and the value generated.

  • Influence applicable functional leadership, strategies, and investments in alignment with the R&D Convergence data integration vision.

  • Translate functional/therapeutic area business challenges and scientific questions into hypotheses that can be tested using data analytics to drive new learning.

  • Partner with R&D Computational Scientists, Data Scientists, and technology teams to advance complex and/or highly novel use-cases with cross-functional dependencies.

  • Identify opportunities and solutions to unleash the full value of Convergence data integration within functional/therapeutic area at an accelerated pace.

  • Lead Matrix teams including scientists, data scientists and MD's at all levels of the technical and medical career ladders.

  • Lead Convergence data integration projects within functional/therapeutic area, allocate resources, manage the budget, and ensure appropriate area expertise.

  • Act as a conduit between the R&D Convergence Core Team and subject matter experts and data scientists within Clinical Development to transfer innovation, knowledge, best practices, and lessons learned.

  • An active member of the community of R&D Convergence Directors across other R&D functions and enable cross-pollination of ideas for broader R&D implementation.

  • Act as a consultant within Clinical Development to help identify where Convergence data integrations and analytics approaches can help answer questions.

  • Influence the talent strategy within Clinical Development to continually enhance the digital skills and acumen of scientists and leaders to align with the Convergence data integration strategy.


Qualifications:



  • Ph.D. with approximately 8-10 years of industry experience or MS with 12+ years of experience in a related field; at least 3 years of experience enabling data analytics and insights within Clinical Development

  • Experience in multiple R&D functions and data domains (eg, preclinical, genomic, clinical, safety, regulatory, real world data, etc.). Considered to have in depth knowledge of drug discovery and development

  • Demonstrated excellence and success in leading data integration and analytic programs to major milestones or insights

  • Effective interpersonal and communication skills and proven ability to collaborate across multi-disciplinary teams and leading and navigating in a matrixed organization

  • Robust understanding of the data analytics value chain from data to decision

  • Proven experience with successfully enabling new digital or data science capabilities that are beyond incremental extensions of the current capabilities

  • Advanced knowledge of machine learning techniques, predictive modeling, statistical methodologies, and visual analytics

  • Experience with big data technologies such as Hadoop, Cloud Computing, and related technologies




Reference: 1152695174

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