Jobs
Benefits & Perks
•Healthcare
•401k
Required Skills
Statistics
Computational Biology
Python
R
Machine Learning
Abb Vie is seeking an innovative and technically proficient scientist to lead the integration of statistical and computational methodologies into analysis workflows for Complex In Vitro Models (CIVM), including organoids, organ-on-a-chip, and advanced multicellular systems. This role will champion multi-modal phenotyping, manage centralized metadata, and drive the development of robust pipelines for hypothesis testing, causal inference, and predictive modeling using multi-omics datasets. The ideal candidate will be instrumental in standardizing and harmonizing data formats and workflows across Immunology sites, collaborating with researchers to build scalable, reproducible data pipelines.
Key Responsibilities:
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Integrate statistical analysis and computational techniques into multimodal data workflows (imaging, spatial omics, etc.) to extract actionable biological insights.
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Collaborate with discovery scientists to design and analyze experiments, translating human-derived hypotheses into mechanistic wet lab assays.
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Lead development of scalable, reproducible pipelines for hypothesis testing, causal inference, and predictive modeling across imaging and multi-omics datasets.
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Guide statistical planning for in vitro (and in vivo studies as needed), including power/sample size calculations, randomization, and reproducibility standards.
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Ensure statistical rigor and appropriate evaluation strategies in interpreting experimental results, supporting go/no-go decisions and milestone reviews, especially for data from in vitro assays.
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Work closely with translational scientists, imaging scientists, bioinformaticians, and pathologists to translate scientific questions into computational solutions.
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Balance innovation with practicality, ensuring solutions are scalable, interpretable, and fit-for-purpose.
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Mentor junior scientists and foster a collaborative, innovative research environment.
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BS, MS, or PhD in Biophysics, Biology, Mathematics, Engineering, Pharmacology or related discipline with typically 12+ (BS), 10+ (MS), or 4+ (PhD) years of experience and a strong track record in computational biology and life science research.
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Minimum 3 years of hands-on experience in computational analysis, algorithm development, and statistics.
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Solid biological domain knowledge and ability to bridge computational and experimental perspectives.
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Exceptional written and verbal communication skills with demonstrated ability to communicate modeling approaches, assumptions, results, and limitations to technical and non-technical stakeholders.
Preferred Qualifications:
- Experience with imaging technologies, functional assays, and data analysis for complex in vitro models.
- Proven record of developing or deploying statistical or AI/ML tools in research, especially in the context of 3D tissue models, organoids or related platforms in a drug discovery or translational research setting.
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
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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.
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We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
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This job is eligible to participate in our short-term incentive programs.
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This job is eligible to participate in our long-term incentive program.
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.
Abb Vie 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
Abb Vie'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, neuroscience, and oncology – and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, YouTube, X, and YouTube.
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About AbbVie

AbbVie
PublicPharmaceutical company.
10,001+
Employees
North Chicago
Headquarters
Reviews
3.7
1 reviews
Work Life Balance
3.0
Compensation
3.0
Culture
3.0
Career
3.5
Management
2.5
60%
Recommend to a Friend
Pros
Good resume experience for entry-level positions
Valuable work experience opportunity
Brand recognition benefits
Cons
Lack of explicit feedback on performance
Limited communication about role expectations
No clear guidance provided
Salary Ranges
88 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Director
Junior/L3 · Clinical Data Scientist - Centralized Monitoring & TA Analytics
1 reports
$123,500
total / year
Base
$95,000
Stock
-
Bonus
-
$123,500
$123,500
Interview Experience
6 interviews
Difficulty
2.8
/ 5
Duration
14-28 weeks
Offer Rate
17%
Experience
Positive 0%
Neutral 33%
Negative 67%
Interview Process
1
Application Review
2
Recruiter Screen
3
Hiring Manager Interview
4
Panel Interview
5
Final Interview
6
Offer
Common Questions
Behavioral/STAR
Past Experience
Technical Knowledge
Culture Fit
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