Adsano Engineering offers a wide range of services in the pharmaceutical sector. From executive selection, recruitment consultancy to staffing, Adsano is dedicated to providing the best suited personnel for the Life Science Industry.
Our client, a global player in the pharmaceutical technology field, based in Basel Switzerland, has an opening for:
The Data Scientist will work alongside scientists and product developers to answer scientific questions using data. Apply and develop analytical methods and predictive models that deliver impact on research and drug develop programs. Implement successful work with the goal of re-purposing it for wider application. Data Scientists will also contribute to the design of AI supported data platform, to make it accessible, useful and engaging for the whole data science community.
Ensures that the scientific question being addressed and interpretation of the data being used is commonly and accurately understood within their team. Contributes to the identification and preparation of chem/biomedical datasets for application in their work. Develops key results and quality benchmarks for data, models and impact in collaboration with scientific users. Develops approaches, methods and models iteratively, communicating results effectively with non-data scientist associates, supporting expert introspection at each stage. Applies their expertise in machine learning, deep learning, data vizualisation and structured/unstructured data analytics towards the scientific goals of their team. Can engineer their solutions. Python, R are required. C, for productization of models and Java, for vizualisation or prototyping, for example, are desirable. The Data Scientist plays a role in knowledge sharing across data science community contributing their insights and research to ensure that we understand state of the art approaches, and can apply them where appropriate.
Key Performance Indicators:
The scientific goals of the team are achieved and the path to user, business and patient impact is clear.
The results of analysis and predictive models can be introspected and measured to gauge scientific validity and likely impact.
Data and user feedback loops drive continuous improvement.
Analytical tools and predictive models build the value of the data42 platform for the wider community over time.
Technical experience on Spark, distributed ML / DL, Python / R libraries, TensorFlow, docker container, ML algorithm
- Strong computer science background with automation/integration is plus.
- Basic understanding of genomics and bioinformatics.
- Understand the difference between ML Runtimes which includes Spark and a number of common libraries bundled with it.
- Able to compile, install and manage configuration of Machine Learning libraries and technologies (Esp. python and R languages, and esp. CUDA, NCCL, XGBoost, TensorFlow).
- Able to install and manage configuration of Machine Learning tools and technologies using docker container solution.
- Understand the distributed ML/DL algorithms and be able to tune and test the algorithms with scalability based on the use case.
- Obsessed about impact
- Collaborative and creative
- Intensely curious
- Constantly seeking better
- A Teamplayer
Duration: 1 year
Any questions? Feel free to contact Annette Deutschbein at + 49 176 313 954 29 or send your CV online.