Pipeline: Data Scientist (all genders)

  • AbbVie
  • Deutschland
  • 17/06/2022
Full time Data Science Data Analytics Artificial Intelligence Software Engineering DevOps

Job Description

Job Description

employment type
full time

Full job description

The Data Scientist drives the development and delivery of advanced analyses, tools, and insights to optimize AbbVie commercial and medical initiatives.

Key responsibilities

  • Applies machine learning and predictive analytics with a focus on regression and linear models in Python to create new insights and real value for our business units
  • Creates profound data visualization in Python
  • Applies (agile) project management and proactive communication to ensure safe & sound project delivery
  • Demonstrates understanding across a wide range of technologies, including big data, data integration, data visualisation and analysis, software development, statistics and machine learning
  • Develops and maintains a good understanding of business priorities, challenges and needs
  • Effectively organises and presents project objectives and progress, clearly contributing to technical documentation and presentations
  • Works with complex data sets, keeping focus on achieving success for our business and our patients
  • Bachelor/Master degree in statistics, mathematics, econometrics, physics, business informatics or a similar field
  • Experience in time series analysis, forecasting, regression and linear models
  • Experience in statistical data analysis, concepts and methodologies and in predictive and prescriptive analytics
  • Experience in machine learning/pattern matching or equivalent scientific field (publications in scientific journals would be considered a plus)
  • Fluency in Python and familiarity with packages such as scikit-learn, statsmodels, scipy and pandas. Knowledge of common data structures and ability to write efficient code in Python
  • Ability to integrate large volumes of data from multiple data sources, conduct deep data dives and statistical analysis systematically
  • Experience creating patient types, HCP segments, unsupervised clustering and data association map and graphs. Experience working with large datasets
  • Good English skills, verbal and in writing