At a Glance
- Tasks: Lead R&D and Data Science, turning complex scientific data into ML-driven products.
- Company: Innovative scientific technology business at the forefront of data and machine learning.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Hands-on leadership role with excellent career advancement potential.
- Why this job: Join a unique role blending science and data to make a real-world impact.
- Qualifications: Background in science with hands-on experience in Data Science and ML.
The predicted salary is between 63000 - 77000 £ per year.
- 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
VP of R&D & Data Science in Scotland employer: AI Connect | Data & AI Delivery Partner
AI Connect is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those passionate about advancing AI technology. With a focus on employee growth, we offer continuous learning opportunities and the flexibility of remote work from Edinburgh, ensuring a healthy work-life balance while contributing to meaningful projects that enhance customer interactions.
Contact Details:
AI Connect | Data & AI Delivery Partner Recruitment Team
StudySmarter Expert Advice🤫
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We think you need these skills to ace VP of R&D & Data Science in Scotland
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
