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Acerca de AbbVie
La misión de AbbVie es descubrir y distribuir medicamentos innovadores que resuelvan los serios problemas de salud de hoy y también abordar los desafíos médicos del mañana. Nos esforzamos por tener una repercusión excepcional en la vida de las personas con varias áreas terapéuticas claves: inmunología, oncología, neurociencia, cuidado de la vista, virología, y salud y gastroenterología de la mujer. Además, ofrecemos productos y servicios de la gama de Allergan Aesthetics. Para obtener más información sobre AbbVie, visítenos en www.abbvie.com. Siga a @abbvie en Twitter, Facebook, Instagram, YouTube y LinkedIn.
Data Scientist Engineer
North Chicago, Illinois ID de la oferta 2206692 Categoría Information Technology División AbbVieAbout AbbVie
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 www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn. Background:
AbbVie’s global Information Research (IR) group has a mission to unlock information that makes cures possible. Within IR, the Data Solutions team works with scientists to provide data management and decision support tools to optimize the efficiency and efficacy of research and development at AbbVie.
Description:
The Data Scientist I position will enhance the scientists’ decision-making capability by creating technology services, data integrations, and scientific applications. This position will work closely with the Drug Discovery organization to develop and enhance chemistry search, modeling, and Computer Aided Drug Design (CADD) processes. Key responsibilities include implementing new tools for data capture, data integration, data visualization, and analysis of large and complex data sets. This opportunity offers the flexibility to work remotely up to two days per week.
Responsibilities:
- Build – through your own efforts and by working with scientists, implement custom solutions/processes that connect data and systems (DELs, ligand screening, 3D molecular design), use software engineering skills to create drug design tools
- Support – computational chemistry packages (open source, internal, vendor), provide solutions and work with downstream systems to support data driven demands
- Evolve- tools and capabilities, stay abreast of new technologies and strive for continuous improvement through creative cutting-edge solutions
- Communicate – ability to communicate with scientists to understand existing workflows and translate business requirements into agile solutions
- Adaptability – given our diverse mission you should be able to move fluidly between different project responsibilities
- Breadth – as a talented and motivated Data Scientist, you can contribute independently to enhancing drug development through database design, API development/integration, custom solution development
Summary
- Bachelor’s degree with 4 years’ experience; Master’s Degree with 2 years’ experience in computer science, software engineering, biology, bioinformatics, chemistry, cheminformatics, data science or equivalent field is required
- Background in life sciences and work experience in the bio-pharmaceutical industry strongly preferred
- Proficiency in Python required
- Experience with structure-based drug design and familiarity with one or more computational chemistry packages
- Preferred technical skills (2 or more): R, Plotly, GraphQL, JavaScript, Node, React, Linux
- Experience developing and integrating APIs (Flask or Falcon preferred)
- Proficiency in SQL, data flow/architecture, ETL
- Knowledge of statistical and data mining techniques
- Previous experience with pipeline software preferred (RapidMiner, Knime, Pipeline Pilot)
- Demonstrated effective communication skills.
- Demonstrated problem-solving and quantitative skills.
- Demonstrated history of successful execution in a fast-paced environment and in managing multiple priorities effectively.
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