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Sr. Data Analyst/Modeler - Pharmaceutical
Ref No.: 19-00956
Location: Summit, New Jersey
Position Type:Contract
Duration: 7+ months
Compensation: up to $70/hr 

Responsibilities:
  • Understand the data landscape, business needs, and propose/implement innovative solutions.
  • Supports data provisioning and advanced analytics to address clinical or business questions.
  • Work with stakeholders to understand and document data assets, data flows, and reporting/analytical needs.
  • Identify areas where data can be used to improve business activities by defining business users' requirements for additional data, metrics, reports, and KPIs.
  • Understand data flows, data collection process, and data repositories. Create and maintain data maps and systems interrelationship diagrams for data domains and systems.
  • Work closely with the data engineers to create optimal physical data models of datasets.
  • Create and maintain metadata and data quality measures and monitoring.
  • Map and blend multiple datasets together in to a coherent domain model that represents the business.
  • Define and govern data modeling and design standards, tools, best practices, and related development methodologies for the organization.
  • Serves as a Subject Matter Expert (SME) within Medical Affairs for existing systems datamart and potential new additions to the data lake / datamart on Synapse big data platform.
Requirements:
  • MUST have Pharmaceutical R&D (Medical or Clinical Affairs) experience.
  • Should have AT LEAST 7+ years of related experience. 
  • Must be a seasoned Data Analyst with multiple years of experience leading and managing large-scale data analysis projects.
  • Strong ability to actively listen, integrate input from diverse sources and successfully translate medical or business questions into data and analytics requirements, and deliver suitable solutions.
  • Knowledge of the mathematical foundations is a plus. For example, statistical inference and forecasting such as time series analysis, multivariate analysis, cluster analysis, and optimization.
  • Ability to explore datasets using visualization and querying tools (e.g. SQL).
  • Ability to utilize Business Intelligence tools (e.g. Tableau, Excel, etc.) to represent insights.
  • Experience working with dimensionally modeled data.
  • Experience with Big Data technology stack (e.g. Hadoop) on cloud environments (e.g. AWS).
  • Familiar with IT processes for system implementation and maintenance.
  • Practical knowledge of data governance, quality and stewardship processes.