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Associate Scientist, Data II

AbbVie · North Chicago, IL · Full time · Information Technology

Posted Aug 18, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

How do you document a graph model so someone can query it without asking you?

What they are checking: Documentation that makes the asset usable.

This is an Associate Scientist, Data II in Information Research at North Chicago, focused on knowledge graph engineering. What do you want to know about who consumes the graph today and how mature it is?

What they are checking: Checking whether the asset has real users before joining to build it.

What would you do

How do you check data quality in a graph, where a wrong relationship is harder to spot than a wrong value?

What they are checking: The data quality duty in a structure that hides errors.

A scientist wants a connection in the graph that the source data does not actually support. How do you handle it?

What they are checking: Holding the model's integrity against a user's expectation.

What makes a knowledge graph genuinely useful rather than an interesting diagram?

What they are checking: Whether they judge the work by what it enables.

About the work

This builds knowledge graphs. Walk me through designing a graph model for something concrete — say, linking compounds to targets to diseases.

What they are checking: Graph modeling on a realistic pharmaceutical problem.

What is the difference between a labeled-property graph and a resource description framework graph, and when would you choose each?

What they are checking: The two model types this posting names side by side.

Walk me through writing a query to find something two steps away in a graph. What makes it slow, and what do you do about it?

What they are checking: Query engineering including optimization, which this posting names.

How do you do entity resolution when the same thing is named three different ways in three source systems?

What they are checking: The entity resolution this posting lists as a query engineering duty.

You are building an ingestion pipeline from a relational source into a graph. What do you test?

What they are checking: Pipeline testing, which this posting names alongside building.

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The full job description

As published by AbbVie.

AbbVie Information Research is seeking an Associate Data Scientist with focus on Knowledge Graph Engineering to design, build, and maintain the semantic data infrastructure that connects information across our domains. In this role you will translate complex source data into well-modeled, interlinked graph structures, write the queries and pipelines that populate and validate them, and collaborate with domain experts, and platform teams to make our knowledge graph a reliable, query able source of truth. This role collaborates with solution architects, product owners, program managers, business analysts, infrastructure teams, and service providers to deliver data and analytics solutions. Responsibilities: • Graph data modeling. Contribute to Design and refine labeled-property and/or RDF graph models — nodes, relationships, properties, and constraints — that accurately represent entities and their connections across source systems. • Pipeline development. Build, test, and maintain ingestion pipelines that extract data from relational, document, and file-based sources, transform it, and load it into the graph using batch and incremental patterns. • Query engineering. Write, optimize, and document Cypher queries for data loading, validation, entity resolution, and downstream retrieval, including support for graph-backed and retrieval-augmented applications. • Data quality and validation. Implement constraints, validation rules, entity resolution (e.g., SHACL or property checks), and automated tests that keep the graph consistent, traceable, and trustworthy. • Performance and operations. Monitor graph performance, tune indexes and queries, and assist with environment management across development, validation, and production tiers. • Collaboration and documentation. Partner with cross functional teams, analysts, and domain subject-matter experts to gather requirements; document data models, lineage, and design decisions clearly for technical and non-technical audiences. Required: • Bachelor’s Degree with 2 years’ experience; or Master’s Degree equivalent education with no additional experience. • Exposure with software development life cycle including Git, testing, and basic CI/CD workflows. • Exposure with at least one graph database (e.g., Neo4j, Amazon Neptune, Tiger Graph, or an RDF triple store) and its query language (Cypher or SPARQL). • Exposure with any data analysis programming languages (e.g., SQL, Python & Apache Spark, SAS & R) including structured and unstructured data. Preferred: • Exposure working with entity resolution, record linkage, knowledge graph construction, vector databases and embeddings, and retrieval-augmented generation (RAG) or graph-RAG patterns is preferred. 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 roleat the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on manyfactors 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 isearned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that areallocable 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 absolutediscretion, consistent with applicable law. ​ AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: https://www.abbvie.com/join-us/reasonable-accommodations.html

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