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Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Project Management, Software Development, Stakeholder Relationship Management.
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Developing and executing model-based analyses including translational PK/PD approaches, population pharmacokinetic models, exposure-response models, clinical trial simulation, disease progression models, quantitative systems pharmacology (QSP) modeling, comparator modeling, thereby strengthening pharmacometrics capabilities on a continuous basis in decision making and driving pipeline impact.
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Skills in experimental design, mathematical problem solving, critical data analysis/interpretation, and statistics. Strategizing and executing modeling of tumor size and survival endpoints including proportional hazards models.
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Ph. D. with 1-3 years of pharmaceutical drug development experience relating to: PKPD, pharmacometrics, mathematics, statistics/ biostatistics, or chemical/biomedical engineering. We are seeking an experienced talented scientist to join the Quantitative Pharmacology and Pharmacometrics - Immune/Oncology (QP2-IO) team in the role of Associate Director QP2-IO team is part of the Global Clinical Development organization and has oversight over drug development aspects related to clinical pharmacology and pharmacometrics of oncology drugs from post-PCC to registration.
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The MEL Specialist may be asked to carry out activities such as: data analysis, in collaboration with technical experts, using appropriate methods such as multivariate regression modeling; data visualization using Microsoft Power BI or Tableau dashboard and use of geospatial data for visualization, mapping etc.
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Developing and executing model-based analyses including translational PK/PD approaches, population pharmacokinetic models, exposure-response models, clinical trial design simulation, disease progression models, quantitative systems pharmacology (QSP) modeling into programs, comparator modeling, thereby strengthening our pharmacometrics capabilities on a continuous basis in decision making and driving pipeline impact.
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Understanding of advanced analytics, BI/data visualization and modeling is a plus. A complete and comprehensive understanding of BI tools, data visualization, data science, general marketing, digital media and CRM, as well as analytics and business intelligence.
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Masters or PharmD with 3-5 years of experience, where "experience" means having a record of increasing responsibility and independence in a similar role in pharmaceutical drug development. To discuss in more detail, please contact your HRBP or Talent Acquisition Advisor.
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Proficiency in Power BI: The candidate should have expertise in Power BI and its various features such as data modeling, report development, visualization, and dashboard creation.
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Formulates relevant and meaningful data analysis through comprehensive data visualization tools, profiling tools, segmentation, as well as leveraging advanced modeling and analytics.
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Data visualization tools such as Power BI or Qlik Sense. As a member of the COE Analytics Modeling Analysis team, you will generate business insights for Client Success Office to help Accenture to improve its processes, boost sales and maximize profitability.
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Data Modeling Skills: The candidate should be proficient in creating data models and have experience with various data modeling techniques such as star and snowflake schemas.
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Strong technical knowledge in numerical groundwater modeling, water resources planning, data management and visualization, and technical writing. Projects include Sustainable Groundwater Management Act (SGMA) compliance and implementation, groundwater basin characterization, water budgets and water accounting frameworks, groundwater-flow and constituent transport modeling, water transfer support, water supply planning, production well design, indirect and direct potable reuse planning, litigation support, and more.
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2+ years’ experience with at least two of these competencies: UX/UI design; data analysis using SQL, R, or similar tools; writing business requirements or user stories to build a software application; project management or agile leadership; financial modeling in Microsoft Excel, VBA experience; business intelligence, data visualization and reporting.
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Validate new genomic tests, bioinformatics software, data analysis processes and data visualization tools. Design and implement bioinformatics tools and process analysis in accordance with defined clinical protocols used for genetic sequence, phenotype analysis, data mining or statistical modeling.
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