Job Title: Real World Evidence Data Scientist

Location: US Remote

About the Job

The US Evidence and Data Feasibility Team in Specialty Care collaborates across functions to develop and implement real-world data strategies for evidence and insight generation projects for US Medical. Partnering with key stakeholders across Market Access, HEVA, Digital Acceleration, and Innovation Teams, as well as global brand teams. The team spearheads robust real-world evidence (RWE) strategies, RWD Analytics, to include sourcing appropriate data, crafting strategic RWE approaches, and supporting the conduct of impactful studies that transform information into insights and evidence to enhance patient care, inform regulatory and access decisions, and improve health outcomes.

• Provide technical expertise for designing and delivering real-world data (RWD) studies, ensuring scientifically rigorous methods.
  
• Identify analytical problems in real-world evidence (RWE) and develop data-driven solutions.
  
• Serve as SME and drive utilization and scaling of data/insight tools and systems.
  
• Design and implement data mining and statistical techniques for RWE datasets, ensuring data quality and integrity.
  
• Develop and maintain programming macros/tools for efficient support, including their development, implementation, and upkeep.
  
• Serve as SME for system upgrades, proposing and supporting system utilities.
  
• Apply machine learning (ML) and artificial intelligence (AI) to extract insights, build predictive models, and align with future technology roadmaps.
  
• Contribute to building a robust RWD/RWE environment, including statistical planning and promoting innovative solutions and operational excellence.
  
• Collaborate with cross-functional teams to translate business needs into data analysis specifications and facilitate effective communication of insights.
  
• Uphold best practices in data science, ensuring compliance with ethical standards and efficient documentation.
  
• Stay current on industry advancements in AI/ML and promote their efficient use across teams.
  
• Implement data visualization to communicate findings and contribute to developing data-driven healthcare solutions.
  
• Maintain clear communication with stakeholders to ensure alignment, manage risks, and ensure smooth project progression.
  

• Master's degree in quantitative fields such as pharmaco-epidemiology, statistics, mathematics, computer science, or related field. PhD is preferred.
  

• Expert knowledge in RWE, pharmaco-epidemiology, health outcomes research, statistical methods, etc.
  
• Experience in statistical programming SAS, R, Python or data base programming (SQL) is a must.
  
• Experience working with routinely collected data (claims databases, electronic Specialty Care health records, registries and various structured and possibly unstructured sources in the healthcare sector within pharmaceutical company settings.
  
• Demonstrated experience in the use of advanced analytics methods. Extensive experience in statistical modelling, causal inference methods (propensity scoring techniques, comparative effectiveness analysis, etc.) and knowledge of advanced artistical techniques (e.g. GAMs, machine learning, deep learning).
  
• Experience working in multiple therapeutic areas - experience in respiratory, immunology and hematological therapeutic areas highly preferred.
  
• Experienced working in complex global matrix teams and with service providers requiring cross-functional collaboration and alignment.
  

• Strong sense of urgency, ownership and proactive attitude to deliver value to our brands
  
• Ability to adapt and communicate messages to a wide range of audiences at all levels (both scientific and commercial), inside and outside of the organization. Able to clearly articulate highly technical methods and results to diverse non-technical audiences to drive decision making.
  
• Apply growth mindset to develop new skills or knowledge.
  

• Advanced programming and statistical computing software skills, expertise with core data science languages (predominantly Python, and nice to have R & Scala), experience working with Snowflake and other different database systems (such as SQL, NoSQL)
  
• Expertise within some of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, optimization
  
• Expertise in RWE study designs and methodologies, including innovative techniques.
  
• Ability to translate complex technical language into easy-to-understand communication with collaborators and stakeholders.
  
• Ability to tell stories with data and knowledge of complex visualization techniques preferred.
  
• Proven experience in managing multiple analytic projects concurrently.
  
• Management of analytical activities of external service providers is highly preferred.
  
• US Experience and exposure to the academic societies, ICDs and clinical practice guidelines is highly preferred.
  

• Fluency in spoken and written business English mandatory
  

• Bring the miracles of science to life alongside a supportive, future-focused team.
  
• Discover endless opportunities to grow your talent and drive your career, whether it's through a promotion or lateral move, at home or internationally.
  
• Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
  
• Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks' gender-neutral parental leave.