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Consultant - RWD Analytics (Hiring for BMS India)

PharmaACE

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3-5 Years
3 months ago
22 Viewed
0 Applied

Job Description

PharmaACE is a growing Global Healthcare Consulting Firm, headquartered in Princeton, New Jersey. Our expert teams of Business Analysts, based across the US, Canada, Europe, and India, provide Analytics and Business Solutions using our worldwide delivery models for a wide range of clients. Our clients include established, multinational BioPharma leaders and innovators, as well as entrepreneurial firms on the cutting edge of science. We have deep expertise in Forecasting, Business Analytics, Competitive Intelligence, Sales Analytics, and the Analytics Centre of Excellence Model. Our wealth of therapeutic area experience cuts across Oncology, Immuno- science, CNS, CV-Met, and Rare Diseases. We support our clients needs in Primary Care, Specialty Care, and Hospital business units, and we have managed portfolios in the Biologics space, Branded Pharmaceuticals, Generics, APIs, Diagnostics, and Packaging & Delivery Systems.

Introduction: If you are keen to work on analytical problem solving, then work in Forecasting/advanced data analytics/sciences to provide consulting to pharmaceutical clients.

Key Responsibilities:

  • Collaborate with cross-functional teams, including researchers, clinicians, market access and regulatory stakeholders, to understand data needs and objectives for RWD analysis
  • Identify relevant real-world data from various sources, such as electronic health records (EHRs), claims databases, registries and other healthcare databases
  • Clean, transform and pre-process real-world data to ensure data quality, consistency and compatibility for analysis
  • Apply appropriate statistical techniques to analyze real-world data and generate insights on research questions or business objectives
  • Conduct observational studies, comparative effectiveness research (CER), patient outcomes research and other types of RWD analysis to evaluate treatment outcomes, safety profiles and healthcare utilization patterns
  • Develop and implement data analysis plans, including study designs, statistical methodologies and modelling approaches
  • Interpret and communicate findings from RWD analysis through reports, presentations and visualizations to stakeholders
  • Collaborate with internal and external teams to design RWD studies, including protocol development, data collection and analysis
  • Stay updated and compliant with the regulatory landscape related to real-world data analysis
  • Contribute to the development and implementation of RWD strategies and best practices within the organization
  • Provide training, guidance and mentorship to junior analysts and team members as required

Qualifications:

  • Bachelor's or Master's (preferred) degree in a relevant field, such as Biostatistics, Epidemiology, Health Informatics, Engineering or a related discipline.
  • Minimum of 3-5 years experience demonstrated in real-world data analysis, preferably within the biopharma, life sciences or healthcare industry.
  • Experience applying statistical and analytical techniques, such as observational study design, CER, patient outcomes research, and data modelling, to analyze real-world data.
  • Experience with R or SAS and SQL required at Working knowledge visualization tools, such as Tableau or Power BI, is desirable.
  • Working knowledge and famaiiarity with relevant statistical methodologies and study designs used in real-world data analysis.
  • Experience or familiarity with the biopharma industry or healthcare domains is preferred.

Skills & Competencies:

  • Strong understanding of real-world data sources, such as electronic health records (EHR), claims databases, registries and other healthcare databases
  • Proficiency in data pre-processing, cleaning and transformation techniques to ensure data quality and compatibility for analysis
  • Knowledge of relevant statistical methodologies, including propensity score matching, survival analysis and regression models, for real-world data analysis
  • Excellent problem-solving skills and the ability to derive meaningful insights from complex real-world data sets
  • Excellent communication and presentation skills to effectively convey complex concepts and findings
  • Ability to work collaboratively in cross-functional teams and manage multiple projects simultaneously
  • Strong attention to detail and accuracy in data analysis and interpretation
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