Associate Director, Real-World Analytics

The  Associate Director, Real-World Analytics uses data and methodological expertise to develop study and protocol designs and statistical analysis plans (SAPs) for the analysis of existing complex health data sets, including real-world data (RWD). This work is conducted in collaboration with Scientists in the Epidemiology and Medical Evidence Generation organizations, and other colleagues as part of matrix teams. These teams work to translate evidence needs into a robust program of studies to support appropriate access to and evidence for GSK medicines. Your work will focus primarily on the oncology research unit.

RESPONSIBILITIES:

The responsibilities listed below outline the scope of the position. The application of these tasks may vary, based upon evolving business needs.

Design and Analysis

• Perform as a biostatistician on non-interventional real-world studies

• Provide expertise in RWD and statistical methodology with asset and RU teams, the broader RWA community, and/or bring that expertise to a matrix team to inform study planning, development, and delivery

• Lead the development and delivery of analysis of existing or new complex health data sets. Responsibilities include: author protocol/statistical analysis plan (includes selecting approach to quantitative bias control, statistical power/precision, sample size), write programming code to conduct statistical analysis, critically review approach and results on an ongoing basis considering design assumptions and knowledge of the data, summarize analytic findings (including limitations) in oral or written form

• Manage a portfolio of work or individual studies to ensure delivery of quality work products to agreed timelines

• Author specifications for analytic data sets for all RWA activities (rapid data queries, retrospective observational studies, and other studies) to ensure appropriate interpretation and implementation of analytic design, in collaboration with RW Data Management and Programming (RWDMP). Review resulting deliverable(s) for accuracy/completeness

• Ensure documentation is appropriate regarding data manipulation, statistical analysis, reporting

• Author, maintain, finalize, and archive project delivery documentation for in-sourced studies in accordance with SOPs where appropriate

• Perform quality control (QC) of work products from other colleagues

• As needed, provide RWD and methodological expertise to support study teams in out-sourced studies

Communication of Results

• Assist with, or be responsible for, oral and written communication of analytic and study results

• Co-author and bring statistical/methodological expertise in scientific publications of the in- or out-sourced RWD studies/analyses

• Effectively present research results to study team and other collaborators, including results interpretation and drawing appropriate inferences based on study design/statistical methods as well as assessment of study limitations

Therapy Area Knowledge

• Understand oncology RU/asset to apply appropriate tools (e.g., variable definitions, code lists) and use appropriate data sources

Leadership and Teamwork

• Build and maintain effective strategic working relationships with internal and external partners to meet business needs

• Maintain currency with methods for the use of existing complex health datasets for research

• Develop in depth knowledge on the assigned asset and act as an RWA consultant within broader Evidence Generation and Epidemiology teams

• Apply innovative statistical methodology and approaches to solve critical problems

• Merge scientific thinking and business knowledge to identify issues, evaluate options, and implement solutions

• Proactively influence team members regarding appropriate research/statistical design and analytics delivery through various engagement forums: at the Value Evidence Team, Integrated Evidence Team, as part of a study team (in-sourced or out-sourced), and in coordination with the RWDMP team

• Mentor team members, in particular RWA scientists and RW Programmers

BASIC QUALIFICIATIONS:

• PhD or MS degree in biostatistics, epidemiology, health economics, health services research, health informatics or related field.

• 3 or more years of experience working with RWD for use in pharmacoepidemiology and/or health outcomes research

• 3 or more years of exper