AbbVie’s mission is to discover and deliver innovative medicines that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people’s lives across several key therapeutic areas: immunology, oncology, neuroscience, eye care, virology, women’s health and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.
AbbVie’s Information Research (IR) group has a mission to unlock information that makes cures possible. Within IR, the AbbVie Library Information Science (LIS) team builds tools and provides services that help AbbVie scientists interact with, manage, and consume knowledge from scientific literature to foster innovation in drug discovery and development. LIS is a global organization, with a large presence in the Lake County headquarters as well as other research sites. We leverage leading technologies and methods to provide AbbVie scientists with our industry’s best capabilities around literature-based knowledge discovery.
This Biomedical Literature Data Scientist role will be part of the Literature-based scientific discovery (LSD) team in the Library Information Science group. The Literature Data Scientist should have a sufficiently strong scientific and technical background to scope and fulfill LSD services. LSD services include knowledge and data extraction, ontology-enabled text and data mining from scientific literature, patents, and other information resources, as well as semantic enrichment, visualization, and library information search services. Additionally, the Literature Data Scientist will effectively collaborate across Library Information Science and other IR teams to deliver LSD services to our clients. The role will help build new analytical text mining methodologies and value-add tools leveraging a combination of commercial and internally developed software.
- Leverage scientific domain and technical knowledge to support AbbVie scientists’ with identifying most relevant information, published knowledge as well as decision-making in R&D projects and deliver customer specific search & analysis solutions.
- Use ontology-based text data mining, scientific data analytics, APIs, and other tools to drive end-user engagement, improved R&D efficiencies, and reveal new discovery opportunities across therapeutic focus areas.
- Provide unique scientific insights and expertise by establishing, streamlining, and automating a knowledge extraction pipeline for collecting, extracting, curating, and visualizing knowledge from scientific publications including statistical context.
- Be a trusted partner of AbbVie’s scientific communities in Knowledge Discovery Projects.
- Collaborate with internal data scientists, information scientists and software developers to design and implement LSD-tailored solutions to meet well-defined stakeholder requirements.
- Monitor continuously newest technology trends relevant for literature analysis and knowledge discovery and establish an external presence through conferences and publications as a SME in analytical text-mining and data extraction.
- Achieve great results while overwhelmingly demonstrating key AbbVie values and behaviors.
- Master degree (5+ years of experience) or Ph.D. degree (0-2 years of experience) in Bioinformatics/ Computational Biology, Cheminformatics, or life sciences (Biology, Pharmacy, Medicine, Pharmacology, Biochemistry, Medicinal Chemistry).
- Solid biomedical knowledge and ability to translate complex scientific questions from research scientists into information solutions.
- Solid programming and informatics/data science/computer science background: Proficiency in Python (intermediate level or higher) required. Ability to understand and modify existing code as well as develop new scripts and set up new data processing workflows. Experience with relational databases, SQL or SPARQL, and web development frameworks would be an additional asset.
- Experience with biomedical information resources (e.g. PubMed), literature and/or patent research, information analysis and data normalization is needed. Experience in text mining, natural language processing, semantic enrichment, ontologies, data mining or machine learning/AI is a plus.
- Strong analytical skills to process, analyze, visualize, and present results. Knowledge of technologies for data analysis and visualization of complex data (e.g. Rest APIs, XML, JSON, KNIME, or Spotfire) as well as knowledge of public domain standard biomedical terminologies (e.g. MeSH, NCIt, HGNC) is desirable.
- Systematic problem-solving, quick learner and superior attention to detail in developing tailored solutions, high degree of reliability and integrity.
- Demonstrates an interest in working collaboratively, cross-functionally, and in inter-disciplinary teams with an ability to effectively communicate, both verbally and in writing to scientists and non-scientists.
- Well-organized and balances taking direction from others (sponsors, partners, clients) with taking initiative to manage multiple projects and learning responsibilities.
- Innate scientific curiosity, technical creativity, and innovative thinking, motivated to break new ground in the field of information/literature analysis and knowledge discovery.
- Fluency in English.
- Open to travel ca. 10 % of the time.
Full-timeJob Level Code
ICEqual Employment Opportunity
At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.