Scientific Reference Data Ontologist
: Job Details :

AbbVie's mission is to discover and deliver innovative medicines and solutions 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, and eye care - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.

Job Description

The Reference Data Architecture team provides comprehensive ontologies and services to manage and semantically map diverse controlled vocabularies throughout our pipeline. We aim at making company-wide data FAIR (Findable, Accessible, Interoperable, Reusable) and unite common meta data in a single reference data architecture. We utilize high-quality data in conjunction with Artificial Intelligence (AI) to derive new insights and improve existing processes with our partners from all over the business. Join this global collaborative team in a flexible work environment to help AbbVie make a remarkable impact on people's lives.

As a Scientific Reference Data Ontologist at AbbVie, you will be responsible for

* Creating and maintaining reference data used within AbbVie and the pharmaceutical industry as a whole (semi-automated)

* Keeping external data sources and data standards up to date, such as Medicinal Products, Compounds, Diseases (building automated processes)

* Participating in the identification and development of new reference data sources and demonstrating applicability in selected projects with business data owners

* Supporting larger R&D-wide convergence initiatives, like our AbbVie R&D Convergence Hub (ARCH), with comprehensive meta data model

* Contributing to building out data governance for reference data and its use

* Creating and maintaining documentation, metrics, operating procedures and training materials

* Demonstrating the benefits of using ontologies in conjunction with our in-house AI/LLM capabilities to produce more accurate and AbbVie-specific results

To do this effectively, strong communication skills will be crucial for cross-functional collaboration, scientific engagement and training. Excellent problem-solving and quantitative skills are needed to identify the right solution and troubleshoot workflows. Building solutions such as dashboards, visualizations, APIs, and analyses will require strong technical skills and experience with appropriate software.

Tools and skills you will use in this role:

* Mature interpersonal communication skills that will enable you working with clients from AbbVie R&D and other business areas

* Strong technical capabilities to programmatically use ontology management tools (e.g. CENtree), triple stores (e.g. Mark Logic), and knowledge graphs (e.g. Neo4J)

* SQL, SPARQL, and Cypher skills (basic queries, table creation, views, and reporting)

* Python, PySpark

* Familiarity with GitHub or other version control tools, project tracking platforms (e.g. JIRA)

* Excellent problem-solving skills

Qualifications

Experiences that make you a strong candidate for this role:

Required:

* Bachelor's degree in relevant scientific field (bioinformatics, cheminformatics, biology, chemistry, biochemistry) and at least 5 years relevant experience OR Master's degree in relevant field and at least 4 years experience

* Experience designing and developing taxonomies, reference data, or controlled vocabularies

* Familiarity with FAIR data principles and common life science data standards

* Knowledge of semantics, data modeling (RDF), and data mining techniques

* Demonstrated history of successful execution in a fast-paced, collaborative environment and in managing multiple priorities effectively

* Demonstrated ability to learn, understand and master new technologies

* Strong written and oral English communication skills

Beneficial:

* Background in life sciences and work experience in the bio-pharmaceutical industry

* Working knowledge of the drug discovery and development process

* Familiarity with life science resources (e.g., public or commercial databases) and descriptive metadata for small molecule and biologics research (e.g. omics)

* Experience with pipeline software (e.g., Apache AirFlow), Machine Learning workflows (e.g., Cloudera ML)

* Working knowledge of using and building APIs

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:

* The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.

* We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.

* This job is eligible to participate in our short-term incentive programs.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion. It is AbbVie's policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because 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, status as a protected veteran, or any other legally protected group status