AbbVie (NYSE:ABBV) is a global, research-based biopharmaceutical company formed in 2013 following separation from Abbott Laboratories. The company's mission is to use its expertise, dedicated people and unique approach to innovation to develop and market advanced therapies that address some of the world's most complex and serious diseases. AbbVie employs approximately 28,000 people worldwide and markets medicines in more than 170 countries.
AbbVie's Information Research (IR) group has a mission to unlock the information that makes cures possible. Within IR, the AbbVie Library 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. We leverage leading technologies and methods to provide AbbVie scientists with our industry's best capabilities around literature based knowledge discovery.
We are creating a new role within the AbbVie Library to provide scientific and operational leadership for literature-based knowledge discovery (LBKD) services. The AbbVie Library is in the process of a transformation where we are migrating the key services we offer from providing awareness of relevant literature to deriving actionable insights from the literature. Key LBKD services we aspire to offer include knowledge extraction, knowledge visualization, library research services, ontology-enabled semantic search, data extraction & analysis from scientific literature, text mining, etc.. The key expectation of this role will be to help our team to define, build out and scale the delivery of these services with our internal team, matrix collaboration partners across the organization, our business partners and external service providers. This manager should have a sufficiently strong scientific background ideally in biomedical research to collaborate with senior R&D scientists to elucidate and prioritize LBKD needs and a sufficiently strong operational background to leverage our people, processes and technologies to meet them. To be successful in this role you must be skilled at helping business partners imagine what is possible, at appropriately managing expectations and at inspiring and influencing colleagues to work together to have a real impact. Additionally you will have to have a keen ability to effectively negotiate scope, timelines, project plans and project budgets related to successfully lead our team in delivering LBKD services to AbbVie.
Leverage scientific domain knowledge to scope and clarify specific requirements for LBKD capabilities with AbbVie scientists translate capability requirements into deliverables / actions that our team of data scientists can collaborate on
Coordinate delivery of new Library capabilities across IR & BTS teams and stakeholders
Be accountable for operational, financial and resource planning for LBKD services
Manage, inspire and bring out the best in a team of highly skilled information scientists
Achieve great results while overwhelmingly demonstrating key AbbVie values and behaviors
Advise IR leadership on industry trends and customer needs related to LBKD capabilities
BA in Life Sciences (Biology, Chemistry), Information Systems, Library Science, Computer Science or related field with 10+ years of experience; MS+ preferred
Scientific domain knowledge and familiarity with pharmaceutical R&D, drug discovery, computational biology, informatics
comfortable with ambiguity and skilled at moving stakeholders towards clarity of requirements
Agile development / design thinking familiarity preferred
Strong customer focus and presence
Comfortable working with staff at all levels of the organization
E xcited about working on a global team with a very diverse customer base
High degree of comfort learning and applying new tools to our work (e.g. Atlassian / Jira for project coordination)
Ability to effectively communicate, both verbally and in writing to scientists and non-scientists
Ability to manage multiple projects with multiple teams and collaborations
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.