Medical Analytics Data Scientist

GSK•Durham, NC

About The Position

In Medical Affairs, understanding how effectively we engage with customers, respond to their needs, share appropriate opportunities that align with their interests, share scientific evidence about our medicines that impact our customers’ clinical decisions for patient care, and deliver credible, timely content that is of high quality are all deemed critically important when determining opportunities to be more customer and patient focused. The purpose of the Medical Unmet Needs Analyst role is to analyze and measure Medical Affairs engagement effectiveness through the use of a variety of data sources and methods/advanced analytics techniques to determine how we can optimize our Medical engagement and content delivery, identify opportunities that will better address and meet customer needs and expectations, and deliver clear insight summaries with recommendations that will drive data driven decision making with the Medical Matrix Teams (MMTs), Medical engagement strategic planning, and other areas within US Medical Affairs. The Medical Unmet Needs analyst will develop advanced analytics solutions aligned with and guided by Medical business priorities and strategies that answer the most critical business questions around Medical measurement, effectiveness/impact, and optimization. This role will support the Director/lead of the team by using advanced analytics expertise to execute and complete analyses and develop recommendations for US Medical Affairs. This role will also evaluate and align US methods with Global measures and focus as appropriate for the US market sharing best practices and approaches with colleagues in Global, Commercial, and R&D. This role will apply standard approaches, frameworks, and methodologies and develop an inventory of measures and studies for reference and benchmarking.

Requirements

BA/BS in a quantitative sciences field required
2 + years of professional experience in developing solutions for business application and applying advanced analytics and statistical skills such as machine learning/AI, advanced decision trees, predictive modelling, experimental design, segmentation, clustering analysis, response modelling and optimization, and/or mix modelling analysis.
2+ years experience with SAS programming and/or statistical software tools such as SAS Enterprise Miner, SPSS for statistical analysis and predictive model development or R; Python, R, etc. for Machine learning

Nice To Haves

Experience applying advanced statistical, analytics, and database skills to solve business problems
Healthcare or life science experience preferred
MA/MS in a quantitative sciences field preferred
2-5+ years (or up to 2 years with an advanced degree) preferred
Proficient business acumen; Knowledge of the healthcare industry and environment; Knowledge of the pharmaceutical industry.
Demonstrated knowledge of data manipulation methods and establishes quality check approaches to develop a deep understanding of the pharmaceutical data assets available for usage with advanced analytics methods and applications
Adept at learning and applying new data, advanced analytics methods and technologies; Possess and demonstrate analytic curiosity to seek out and develop potential solutions and drive continuous improvement; motivated by challenging, complex problems
Strong understanding of statistical or other advanced analytics methods appropriate for a business problem
Strong communication and presentation skills (both oral and written) plus project management skills; Consulting experience preferred
Effectively builds relationships and collaborative partnerships across teams to develop a solution
Effective at presenting complex, technical information, concepts, and analysis in a compelling and persuasive manner to non-technical audiences
The ability to focus and thrive in times of change
Knowledge of multivariate statistics (cluster analysis, regression models, experimental design, etc.)
Understanding of machine learning, supervised and unsupervised modelling techniques, and probabilistic models of complex systems with "big data" sources
Experience with SQL and in-database processing in a Teradata environment as well as data visualization tools such as PowerBI, Tableau, JMP, Qlikview, etc. a plus.

Responsibilities

Actively contribute to the development of high quality, advanced analytics solutions and insights for the TAs and US Medical Affairs on measurement and effectiveness/impact as well as resource effectiveness and resource allocation/ strategy adjustments
Deliver clear, actionable recommendations from the analytic applications in the areas of: Channel effectiveness, diagnostics, and performance measurement across all channels and customer types across TAs and overall USMA Resource allocation and optimization across products and channels for the TAs Experimental design (test/control) analyses Simulation and what-if scenarios for Medical engagement strategic planning
Develop, apply, and align best practice standards for measurement effectiveness and optimization analytics based on an understanding of the Medical Affairs priorities and challenges, the business model, and the healthcare environment
Develop and maintain an inventory of measures and studies for reference and benchmark comparisons.
Develop innovative approaches for modeling events, customer/patient knowledge, customer/patient understanding, and customer/patient behavior (as appropriate for Medical Affairs) to better isolate channel effectiveness.
Proactively contribute to the team with advanced analytics ideas and methods for improved and more efficient decision making with measurement, effectiveness, resource allocation, optimization, and impact for Medical Affairs.
Identify and proactively seek out opportunities for improved advanced analytics methods, approaches, and applications aligned with and guided by Medical priorities by researching industry trends, methods and best practices, academic/external methods applied successfully in business or Medical affairs, and evaluating external benchmarks for competitive value.
Ensure advanced analytics method application excellence with attention to detail and quality check measures in place
Share best practices, demonstrate and further develop business acumen, and ensure customer focus and alignment with critical priorities when developing solutions.
Build advanced analytics application expertise and earn the trust of stakeholder partners through demonstrated learning, and business acumen development
Continually seek out and build business knowledge and depth for appropriate business context with analytic recommendations.
Partner with colleagues in Medical Analytics and Commercial Insights to ensure application of best practice research and analytics methods and to integrate insights (as appropriate) for a holistic and comprehensive product, TA, or enterprise view to influence strategic decisions for the future
Demonstrate effective communication and drive efficiencies through partnership and collaboration with cross-matrix partners
Partner closely with the Medical Measurement Effectiveness and Optimization manager and demonstrate development of business understanding and the key priorities of focus
Communicate clearly and simply for stakeholder understanding
Translate technical concepts into easy to understand key points and recommendations
Use storytelling approaches, simple visuals, and clear written and verbal communication to effectively share key insights that inspire usage for data driven decision making.