Data Scientist for Published Clinical Evidence & Competitive Intelligence Insights

Data Scientist for Published Clinical Evidence & Competitive Intelligence Insights

AbbVie

Ludwigshafen, Germany

The Data Scientist will join the Solutions for Published Insights and Client Enablement (SPICE) team, supporting AbbVie’s R&D, CBSO and other business functions enterprise wide. SPICE provides business partnership, resource consultancy, ad-hoc research support for business-critical questions, knowledge and insights mining and analysis, as well as designing and building innovative self-service solutions for insights generation from published resources and internal knowledge. This includes literature, patent, conference, news, clinical trial, and competitive intelligence data such as competitor pipelines.

The Data Scientist should have sufficiently strong background in both science and technology to fulfil this role and demonstrate high motivation to expand their knowledge in a pharma context and as SME for key client groups. The role is expected to collaborate effectively within SPICE, EKA, and the larger IR organization, driving impactful results for all of AbbVie. Responsibilities include developing novel AI-based capabilities for extracting, harmonizing, and monitoring published clinical trial data, real-world evidence, and other competitive insights. They will closely collaborate with internal expert teams to define requirements and integrate manually curated data and insights, thereby supporting pipeline strategy, corporate strategy, and commercial teams with essential intelligence for advancing AbbVie’s pipeline.

Make your mark:

• Leverage scientific domain and technical knowledge to support clients across AbbVie with the most relevant information and published insights for decision-making. Key focus: Competitive Intelligence, Corporate and Pipeline Strategy groups and data;
• Build and design new methods and automated workflows to systematically identify, extract, normalize and database key insights and evidence from publications as well as other published sources using GenAI and other state-of-the-art technology and data science solutions;
• Work with key stakeholders and expert teams to identify novel sources for manually curated competitive intelligence and clinical trial data and integrate in existing workflows to democratize access across AbbVie;
• Support efforts for streamlining AbbVie’s systematic literature review process and knowledge extraction from (full-text) publication resources;
• Provide unique scientific insights and expertise by designing and developing solutions for finding, extracting, curating, and visualizing knowledge from published and internal data;
• Monitor and be attuned to new technological trends relevant for knowledge analysis and insights discovery;
• Achieve great results, while demonstrating key AbbVie values and behaviors.

Qualifications:

This is how you make a difference:

• Bachelor’s degree (7+ years of experience), Master’s degree (5+ years of experience) or Ph.D. degree (0-2 years of experience) in life sciences, medicine, pharmacy, bioinformatics, biomedical/clinical data science or related field;
• Solid scientific domain knowledge in late-stage pharmaceutical development, including Medical Affairs, Clinical Development, Pharmacovigilance, Health Economics & Outcomes Research (HEOR), or Epidemiology, shown through education or work experience;
• Proficiency in Python is required and experience in front-end technologies (HTML, JavaScript, CSS, React) as well as basic working experience with Linux/Unix-based OS or Docker is a plus;
• Competence in using GenAI models for knowledge extraction as well as basic understanding of agents and agentic workflows (MCP, A2A);
• Experience in analyzing publications, especially literature, is essential. Ideally also experience with drug pipeline or trial CI databases (e.g. Clarivate’s Cortellis Competitive Intelligence, Citeline’s Trialtrove or Pharmaprojects);
• Strong analytical skills to process, analyze, visualize, and present results to variety of audiences. Knowledge of common technologies and formats for retrieval, analysis and visualization of complex data. Experience using relational databases and SQL (Oracle, Apache Hadoop);
• Systematic problem-solving mind, quick learner and superior attention to detail in developing tailored solutions, high degree of reliability and integrity;
• Ability in working cross-functionally and in inter-disciplinary teams, while communicating effectively, both verbally and in writing, with scientists and non-scientists. Comfortable in a fast paced work environment with constantly shifting priorities;
• Innate scientific curiosity, technical creativity, and innovative thinking. Motivated to break new ground in the field of information analysis and insights generation;
• Excellent written and oral English language skills as well as the openness to travel (10%).