Senior Data Scientist I – Bioassay Data Scientist

AbbVie

North Chicago (IL)

On-site

USD 110,000 - 180,000

Full time

35 hours ago

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Benefits offered by this job

Paid time off

Medical/dental/vision insurance

401(k)

Short-term incentive programs

Job summary

AbbVie is seeking a scientist to join the Global Research, Informatics & Platform Solutions team. You will help define, steward, and expand our bioassay knowledge graph, translating workflows into data solutions and building data visualizations/AI-enabled tools to accelerate drug discovery.

You will partner with laboratory scientists and technology teams to harmonize data, integrate diverse datasets, and deliver scalable analytics pipelines across platforms.

Qualifications

Bachelor's Degree with 6+ years’ experience, or Master’s with 5+ years, or PhD with 0+ years.
Background in life sciences, biology, or related field.
Working knowledge of drug discovery & development processes.
Understanding of biological ontologies.
Experience with bioassay data.
Familiarity with knowledge graphs to enhance biology data.
Ability to interface with stakeholders across IT and science teams.
Strong data visualization skills and experience with flexible plotting libraries.

Responsibilities

Harmonize biology data and derive knowledge statements for the knowledge graph.
Communicate with scientists to understand workflows, data flows, and requirements.
Design and implement solutions that visualize and analyze complex multi-platform data; build data pipelines.
Integrate internal and external datasets and leverage ontologies.
Provide solutions to performance issues and support bioassay-data-driven needs.
Demonstrate proficiency in data storage, transfer, integration, visualization, and analytics technologies.
Work on multiple projects concurrently and adapt to changing priorities.
Explore automation, AI, and analytics to improve scientific workflows.

Skills

Bioassay data

Knowledge graphs

Data visualization

Python

Spotfire

ggplot2

plotly

Communication

Independent work

Cross-functional collaboration

Education

Bachelor's Degree

Master's Degree

PhD

Tools

Spotfire

Python

ggplot2

plotly

ELN/LIMS

Job description

About AbbVie

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 including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Company Description

About AbbVie

Job Description

The Global Research, Informatics & Platform Solutions team within the Information Research (IR) Division partners with scientists and research organizations across AbbVie to unlock the value of scientific data. By enabling effective management, integration, and use of high-quality research data and delivering informatics platforms and decision-support capabilities, the team helps transform complex scientific information into actionable insights that accelerate discovery, strengthen scientific decision-making, and improve the efficiency and effectiveness of research and development. The role serves as a key bridge of expertise between laboratory scientists and technology teams and is responsible for defining, stewarding, and expanding our bioassay knowledge graph, translating scientific workflows into data solutions, and building data visualizations/AI-enabled solutions that accelerate drug discovery.

Responsibilities

Harmonization – apply previous biology/biochemistry wet lab experience and strong knowledge of biology data to harmonize knowledge graph data & derive knowledge statements.
Communicate – ability to communicate with scientists from Discovery teams to understand existing workflows, data flows & gather requirements.
Collaborative Design – understand the client’s needs, propose solutions, and independently develop appropriate solutions.
Build – Conceive, design, and implement technology solutions that integrate, visualize, and analyze complex multi-platform data; build pipelines to integrate data into systems/warehouses.
Integrate – understand the value in capturing data properly, integrating internal & external data sets and leveraging ontologies.
Support – provide solutions to performance-related issues and work with downstream systems to support bioassay-data-driven demands.
Technical Proficiency - Demonstrate high proficiency in technologies for data storage, transfer, integration, visualization, and advanced analytics.
Adaptability – ability to work on multiple, sometimes very different, projects at one time.
Breadth – contribute independently to a wide variety of projects related to enhancing drug discovery & development.
Evaluate - implement automation, AI, and advanced analytics opportunities to improve scientific workflows.

Qualifications

Required

Bachelor's Degree and 6 years of experience; Master's Degree and 5 years of experience; PhD and 0 years of experience
Background in life sciences, biology, or equivalent required,
Working knowledge of drug discovery and development process
Understanding of biological ontologies
Experience working with bioassay data required.
Understanding of knowledge graphs with ability to enhance our existing biology data
Dedicated team player who can interface with stakeholders from a variety of internal IT disciplines (DBAs, architects, developers, etc.) and external customers (discovery scientists, therapeutic area scientists, etc.)
Strong familiarity with data visualization and pipelining tools such as Spotfire, or equivalent
Demonstrated data visualization skill and experience with flexible plotting libraries (D3, ggplot2, plotly) and/or visualization platforms.
Ability to work independently, multi-task, and work within timelines.
Outstanding verbal, written and interpersonal skills for cross-functional collaboration, including documenting and presenting technical solutions to non-technical stakeholders.
A self-motivated learner and thinker with a hands-on approach

Preferred

Demonstrated technical proficiency in the pharmaceutical industry highly preferred.
Previous in vitro biology wet lab experience preferred.
Experience with LIMS, ELN, and other scientific software preferred.
Strong programming proficiency in Python (and other modern languages) desired.

Additional Information

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 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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