VP of R&D & Data Science
Edinburgh
£85,000 – £95,000
AI Connect are partnering with an innovative, scientific technology business to appoint a VP of R&D & Data Science into a genuinely interesting leadership role at the intersection of science, data and machine learning.
This isn't a traditional VP of Data Science position.
We're looking for someone who started their career in a scientific environment – perhaps chemistry, biology, bioinformatics, analytical science, physics or a related discipline – and has since developed into an accomplished, hands-on Data Scientist / ML leader.
You'll lead the Data Science capability while working closely with an established R&D function, including a Director of R&D who will report into this position.
You don't need to have managed a huge scientific organisation.
What you do need is enough scientific depth to understand how experiments are designed, how scientific data is generated and where issues such as experimental methodology, ground truth, confounding and environmental variability can fundamentally affect the models being built from it.
From there, you'll bring the data perspective.
You'll help ensure experiments are designed with the downstream data requirements in mind, lead the approach to modelling and validation, and ultimately help turn complex real-world scientific data into robust ML-driven products.
We're particularly interested in people with experience across areas such as:
• Scientific / experimental R&D environments
• Data Science & Machine Learning
• Experimental design and statistical methodology
• Noisy real-world sensor, instrument or time-series data
• Signal processing, classification or predictive modelling
• Taking scientific or ML products from experimentation towards real-world deployment
• Python / R / similar hands-on analytical tooling
Experience within chemistry, bioinformatics, life sciences, diagnostics, sensing, spectroscopy, analytical science or similar scientific domains could all be highly relevant.
This is still a hands-on technical leadership role. We're not looking for someone who has moved completely away from the data - you'll still be comfortable getting into difficult datasets, challenging assumptions and working through complex analytical problems yourself.
If you have the required skills and experience, then please apply for more details