Job Description
Compensation: Competitive package including equity options
Location: London or Germany (Hybrid)
Type: Full Time, Permanent
SciQ are partnering with an exciting startup founded by a highly accomplished team with a track record of building successful companies. They bring the platform business model of company building to drug discovery and development. Our client is now building an AI platform to accelerate and improve discovery and development of new compound classes. They have a rare opportunity for a Cheminformatician to join the team and play a significant role from a very early stage.
This is an opportunity to join a fast-paced entrepreneurial environment, where you will have a significant influence on company strategy and performance.
Roles and responsibilities will include (but are not limited to):
- Design, develop and implement robust data processing workflows and storage environments
- Collaborate with both scientific & tech teams to provide chem-/bioinformatics expertise, including on data collection and standardization, database structure, workflow development, algorithmic design, data analysis, and visualization
- Work hand in hand with a machine learning engineer to implement these core algorithms into the technology platform; build and supervise a team of data scientists over time
- Coordinate and perform data analysis efforts on different projects; communicate results to diverse audiences, including project teams, collaborators, and customers
- Use good programming practices, documentation and reproducible research.
- Dissemination of results, where appropriate, in the form of conference presentations and research articles
- Stay abreast with new technological advancements and analyze them for potential inclusion in the platform
Experience and skills:
- Qualification: Advanced Degree in Cheminformatics, Bioinformatics, Computational Biology, Computational Chemistry, Biotechnology, Data Science, or related discipline
- 3-5+ years relevant experience handling & analyzing chemical and biological data in academia or industry
- Experience with building large chemical databases associated with bioactivity data and other biological endpoints
- Familiarity with SQL, Python, scikit-learn; chemical toolkits (e.g. RDKit); chemical workflow environments (particularly KNIME); and chemical cartridges
- Software development experience, familiarity with version control tools, and reproducible research practices
- Strong oral & written communication skills in English