At a Glance
- Tasks: Lead research and develop cutting-edge neurosymbolic AI language systems.
- Company: Join UnlikelyAI, a pioneering company in AI innovation.
- Benefits: Enjoy hybrid work, mentorship opportunities, and a collaborative team environment.
- Other info: Great career growth potential in a dynamic and supportive setting.
- Why this job: Make a real impact in AI while working on exciting projects.
- Qualifications: Experience in applied research and strong development skills in AI.
The predicted salary is between 70000 - 90000 £ per year.
Unlikely AI is seeking a Staff Applied Scientist in London to lead applied research and contribute ownership over production-grade language generation systems.
The role blends research leadership with hands-on development in neurosymbolic AI and large language models.
You will mentor colleagues, collaborate across teams, and drive end-to-end projects from literature review to deployment, in a hybrid work setup near Holborn with potential for team days and remote collaboration.
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Hybrid Staff Applied Scientist: Neurosymbolic AI Leader in London employer: Unlikely
At UnlikelyAI, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to innovate and grow. As a Staff Applied Scientist, you'll not only lead cutting-edge projects in neurosymbolic AI but also have the opportunity to mentor and develop your colleagues in a collaborative environment. With a hybrid working model near Holborn and unique benefits like a tax-efficient EMI share option scheme, we offer a rewarding experience for those looking to make a significant impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Staff Applied Scientist: Neurosymbolic AI Leader in London
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We think you need these skills to ace Hybrid Staff Applied Scientist: Neurosymbolic AI Leader in London
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Unlikely, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Unlikely. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Unlikely
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Unlikely!
✨Prepare for Case Studies
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.
