Director, Real World Analytics/Value Evidence & Outcomes
- Collegeville, PA
Site Name: UK - London - Brentford, USA - Pennsylvania - Upper Providence
Posted Date: Nov 4 2020
Director, Real World Analytics/Value Evidence & Outcomes
The Real-World Analytics (RWA) Scientist 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) or randomized clinical trial (RCT) data. This work is done in collaboration with scientists in the Value Evidence and Outcomes (VEO) organization 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 GSK medicines.
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
- Manage a portfolio of work or individual studies to ensure delivery of analytics to agreed timelines and quality
- Share RWD and methodological expertise with asset and therapy area (TA) 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 complex health data sets. Responsibilities include: author protocol/SAP (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
- Author specifications for analytic data sets for all RWA activities (rapid data queries (RDQ), 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 statistical colleagues
Communication of Results
- Assist with, or be responsible for, oral and written communication of study results
- 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 TA/asset in order to apply appropriate tools (e.g., variable definitions, code lists) and use appropriate data sources
Leadership and Teamwork
- Maintain currency with methods for the use of existing complex health datasets for research
- Apply innovative 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 (VET), as part of a study team (in-sourced or out-sourced), and in coordination with the RWDMP team
- Mentor junior staff and team members
Why you? Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:
- MS in a quantitative discipline such as epidemiology, health economics, health services research, health informatics, or biostatistics
- Experience working with RWD for use in pharmacoepidemiology research with good practical knowledge of biostatistics applied to clinical/epidemiological research
- Experienced SAS programming skills: SAS Base, SAS Macros, SQL, SAS procedures: FREQ, PHREG, etc. other statistical analyses programming language (e.g., R, Stata, Splus) is an asset
- Passionate about working hands-on with data, and proficient in manipulating large, complex datasets and preparing supporting documentation for QC
- Excellent problem-solving and analytical skills and enjoy finding efficient and innovative solutions to challenging problems
- Self-reliant with the ability to deliver robust, timely, high-quality analytics
- Enthusiastic collaborator and enjoy working on a wide range of projects and requests across multiple TAs
- Fluent in written and spoken English to effectively communicate and able to articulate complex concepts to diverse audiences
- Sense of urgency; achievement oriented
- Ability to work with a multi-disciplinary team
- Ability to work with a minimum of supervision
- Having a responsibilities-oriented way of working
- Comfortable with rapid, flexible, innovative working and decision-making
- Excellent organizational and planning skills, analytical mind
- Good communication skills
Preferred Qualifications: If you have the following characteristics, it would be a plus:
- A good understanding of drug development processes and strategies, with proven ability to apply innovative statistical thinking to meet project and/or business objectives
- PhD degree in a quantitative discipline such as epidemiology, health economics, health services research, health informatics, or biostatistics
- Great experience working with RWD for use in pharmacoepidemiology research with good practical knowledge in biostatistics applied to clinical/epidemiological research
Interested in Joining the Team? Please apply via our online portal providing your CV and Cover Letter.
Please ensure you apply before the 25th November 2020 to ensure you're in the running!
(Please take a personal copy of the Job Description, as this will not be available online post closure of the advert)
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