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AbbVie’s mission is to discover and deliver innovative medicines 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, eye care, virology, women’s health and gastroenterology, in addition to products and services across its Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.

Data Science, Toxicology

North Chicago, Illinois Req ID 2207407 Category Research and Development Division AbbVie

The Computational Toxicology group functions to develop, refine, and bring awareness to in-silico methods that may help predict and understand safety and toxicology for small and large molecules.  Team members will gain exposure to a wide range of safety-related datasets ranging from biology, pharmacology, toxicology, and chemistry to help with predictive modeling and data analysis.  Using these datasets, the team hopes to apply data science and machine-learning methodology to better visualize the data and help identify novel and mechanistic associations.


  • Collaborate with research and bioinformatics scientists to conceive informatics analysis strategy leveraging advanced machine learning/AI algorithms to support discovery and pre-clinical safety studies.  Specific applications can be but not limited to transcriptomics, bioactivity, in vitro/vivo safety data and molecular data integration, etc.
  • Identify and process relevant internal and external safety datasets and knowledge resources. Propose and execute computational research to identify associations across safety features by leveraging and harmonizing datasets
  • Develop tools and user-interfaces that incorporate learnings from computational work to assist team members to evaluate and predict safety outcomes
  • Communicate results and methods verbally and in writing for scientific and non-technical audiences
  • Bachelor’s Degree with 4 years’ experience or Master’s Degree with experience in Statistics, Computer Science, or a related quantitative field. Background in life sciences or work experience in the pharmaceutical industry preferred.
  • Experience with data science and a variety of coding languages and packages, such as R, Python etc. Expected proficiency in at least Python and R.
  • Knowledge of data mining, cleaning and transformation techniques, such as dimensional reduction, normalization, standardization, imputation, aggregation, and performing exploratory analysis prior to statistical analysis or machine learning
  • Familiarity with modern relational databases and/or distributed computing platforms Big Data, and their query interfaces, such as SQL, Impala, Spark, PySpark and Hive.
  • Experience using visualization techniques for presenting data and analysis as dashboard in tools such as R/Shiny, ggplot, SpotFire, and Custom web-based solutions.
Significant Work Activities: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Travel: No
Job Type: Recent Graduate
Schedule: Full-time

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