Safety Data Scientist The Safety Data Scientist will lead projects in deriving insights related to patient safety through the analysis of data from clinical trials, internal and external safety databases, real-world data from EMR and claims using statistical, machine learning and / or AI methodologies. This will include the ability to select and manipulate diverse types of data (structured and unstructured) prior to analysis, the development of advanced modelling algorithms, the presentation of data to help impart insight as well as the ability to articulate the implication of such insight. As well as undertaking analytics activities, this role will help define and build data science enablers such as good practise frameworks, validation strategies, algorithm libraries and enabling tools and components. She/he will support the development, training and coaching of junior members of the safety analytics team ensuring the delivery of relevant high-quality algorithms and insights. Importantly she/he will typically engage directly with stakeholders from PS CoE and TA groups towards understanding the problem, developing the appropriate analytics strategy and ensuring value creation from the insight. A key part of this senior role will be the evangelization of possible analytics safety solutions and the Art of the Possible in this emerging field within and outside PS CoE.
Typical Accountabilities:- Lead analytics projects in close partnership with diverse stakeholders from PS CoE and PS TA teams
- Develop an understanding of organizational priorities and early insight into changing project needs
- Propose and deliver analytic solutions including applied statistics and machine learning to elucidate key insights form data or build self-service tools
- Develop software solutions or self-service tools with the appropriate compliance requirement
- Translate unstructured and complex safety questions into the right data science problems, predictive models, statistical tests, and analytical solutions
- Select and apply right methods for analysis and interpret the results in close partnership with PS stakeholders
- Develop a robust understanding of safety, clinical, and real-world data sources, their structure, provenance, and quality
- Apply data wrangling when necessary and always ensure good programming practise are used
- Train, lead and mentor junior members of the group
Delivers subject matter expertise for analytics across stakeholders from the PS organization.
Maintain an external focus and visibility through attendance at external meetings, conferences, consortia, and where relevant, support external presentations / publications to validate the corporate reputation of client
Education, Qualifications, Skills and Experience
Essential:
MSc or Ph.D. degree in Computer Science, applied statistics, or related quantitative field.
Expertise in programming languages, especially R/ Python and SQL.Understanding of widely used statistical methods and machine learning algorithms
Experience visual analytics tools, cloud computing, and version control
Ability to translate a business problem to a data science problem and to reverse-translate the results to tell a compelling story
Highly developed analytical and conceptual thinking, with the ability to understand multiple, complex business needs and to prioritize them
Familiarity with clinical, safety, and real-world data
Proven record of leading analytical solutions to address research/business problems.
Experience of leading projects in a matrix environment with multiple stakeholders
Excellent written and verbal communication skills
Proficient in English, both spoken and in writing
Exerting Influence Without Authority.
Desirable:
Prior experience of working in a pharmaceutical or biotechnology company
Experience with longitudinal data analysis
Familiarity with deep learning algorithms applied to natural language processing
Experience of enabling innovation and managing change involving many stakeholders
Experience in working across different geographic locations, organizations, and cultures.
Ability to train, develop and mentor junior data scientists
Ability to spot new opportunities for applying analytics solution
