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Draw on experience with Github, machine learning, advanced programming in SQL and Python, Cloud computing such as AWS, Google and Azure, Tableau, and Simio to design, develop and implement a broad array of business analytics that solve complex problems in a computationally efficient manner by leveraging advanced understanding of statistics and data science.
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Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning, data visualization and other quantitative methods.
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Our data analytics and software platforms support data science, commercial operations, real-world evidence, and cloud information management. High proficiency on data analysis using tools like R, Python, SQL (atleast one required/Python preferred) Qualitative skills: Independent contributor/Self starter Good communication and presentation skills to present work to Executive Leadership team Able to commute to client location - 25% Extensive knowledge of various pharmaceutical industry data sources such as: IQVIA (xPonent, xPonent PlanTrak, NPA, DDD, HCOS, and Patient Level data) or Symphony data.
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Work closely with our data engineering and data science teams to design and optimize data pipelines and ensure efficient and reliable data processing. Collaborating with data engineering and data science teams to understand data requirements and design optimal data pipelines.
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Master's degree from an accredited college or university in health economics and outcomes research (with strong analytical skills), statistics, mathematics, psychometrics/psychology, epidemiology, computer science or related fields.
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Associate of Science degree from an accredited respiratory therapist program, required. Associate of Science degree from an accredited respiratory therapist program, required. Credentialed as a Certified or Registered Respiratory Therapist (CRT or RRT) from the National Board of Respiratory Care (NBRC), required.
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Collaborate with Architecture, Infrastructure and Data Science teams to translate their needs or challenges into production-grade Artificial Intelligence and Machine Learning deployment architectures for batch, real-time streaming deployments.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; Data Processing/Analytics/Science, Computer and Information Science, Statistics.
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Incorporate core data management competencies including data governance, data security and data quality. You will leverage your ability to design, build and deploy data solutions that capture, explore, transform, and utilize data to support Artificial Intelligence, Machine Learning and business intelligence/insights.
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Evaluates clinical and biomarker data sets from biostatistics and data science, contributes to data analysis, data reviews and interpretation, authors and ensures the quality of study reports and other relevant documents, presents results and insights to internal core teams accompanied by specific, decision making, recommendations.
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Purpose of Role: Join our dynamic Supply Chain team as a Power BI Developer where you will harness data from our data lake, integrating inputs from our ERP and third-party vendors to create compelling, informative visualizations that drive business decisions.
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The role leads the US TA insights team across all aspects of identifying key business questions (KBQs), leading the development and execution of an Integrated Insights Plan (IIP) with its various components such as Primary Market Research (PMR), Forecasting (FC), Business Analytics (BA), data strategy, human insights (behavioral science-led) and Competitive Intelligence (CI) in collaboration with internal partners and external vendors.
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Knowledge of social science research methodologies, data applications and repositories, and legal and government information sources. Ability to assess curricular and research needs in social science disciplines, select materials, and build library and data services to meet those needs.
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Coach managers to effectively identify clients' business pain points, short-term and long-term business objectives, propose and scope out HEOR/RWE studies with clear business and statistical rationales on all aspects of RWE databases studies/analyses including objectives, project framework and phases, study design and methodology, data source identification and comparison, protocol development, statistical analysis and interpretation, project timeline and resource, roles and responsibilities.
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To thrive in this career as a Principal Data Scientist (Generative AI) for the Innovation Labs team, you will apply your knowledge of Python and other object-oriented programming languages to ADP projects.
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data science jobs Title: associate in Whippany, NJ
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