Opportunity Description
The Industrial Affairs data scientist has a key role in defining, executing data science solutions like, predictive models (supervised, unsupervised), data pipelines or graph-based approaches. Developed models will be integrated in existing could-based applications and deployed on a global scale. Moreover, the IA Data Scientist will drive the development of novel data products within our data platform as well as executing/evaluating the proof of concept (cf. micro apps) together with clients.
ROLE REQUIRES STRONG INTERFACES WITH:
- Client's IA Data transformation leader
- Digital Product Owners
- ITS organization
- Fit4Future change leaders
- Other data scientists across the digital DS organization
Essential experience:
- Master’s degree in mathematics, computer science, engineering, physics,
statistics, economics, computational sciences or a related quantitative
discipline and 5+ years of Data Science experience, or PhD + 3years of with
relevant work amp; domain experience. - Direct experience with any of the following techniques: advanced NLP
modeling, machine learning, semi-supervised, deep learning, graph neural
networks, Bayesian networks and numerical optimization - Experience deploying (micro) apps cf. Shiny or Flask
- Visual analytics and/or data story telling with Power BI or other
- Experience with some aspects of pharmaceutical operations, specially
manufacturing - Expertise with the core data science languages (such as Python, R), and
familiarity amp; flexibility with data systems (e.g. SQL, NoSQL, knowledge graphs) - Comfortable working in cloud and high-performance computational
environments (e.g. AWS, Apache Spark) - Excellent written and verbal communication, business analysis, and consultancy skills
- Experience working in an agile environment
Desirable experience:
- Disciplined AI / ML development (CI / CD, Orchestration)
- Experience with Tableau or Power BI
- Regulatory, GxP, or similar standards
- Orchestration, AWS stepfunctions, Apache Airflow or Kedro
Requirements
Data Scientist Responsibilities:
- Build models, algorithms, and performance evaluation by writing highly
optimized, deployable code and using state-of-the art machine learning
technologies - Define and implement architectures for predictive algorithm for cloud-based
manufacturing application - Industrializing solutions together with small teams (pods, scrum) in an agile
way of working - Proficient at collecting and mining data from disparate data sources, and
willing to dig deeper and understand the process that creates the data - Work with a data lake as well as graph databases (cf. neo4js and AWS
Neptune) - Use data analysis, visualization, storytelling, and data technologies to scope,
define and deliver AI-based data products to accelerate and data product
deployments - Developing digital data products and pipelines for IA that scale
- He/she will be able to generate work product that includes interactive
visualizations, presentations, publications, web applications, predictive
algorithms, and API - Document insides and architecture as well as planning using Jira/Confluence