At a Glance
- Tasks: Lead groundbreaking machine learning research and mentor aspiring scientists.
- Company: Join a forward-thinking firm at the forefront of finance and technology.
- Benefits: Access to top-tier datasets, competitive pay, and a collaborative workspace.
- Other info: Engage with the academic community and enjoy excellent career growth.
- Why this job: Shape the future of machine learning while making a real-world impact.
- Qualifications: PhD in a quantitative field and proven research leadership experience.
The predicted salary is between 80000 - 100000 £ per year.
Responsibilities
- Help define and accelerate the long‑term machine learning research agenda within Systematic Equities.
- Identify emerging research directions, evaluate new developments in machine learning, and translate promising academic advances into practical applications.
- Act as a scientific leader, mentor, and advisor across the research organisation.
- Represent the company externally through participation in leading conferences and engagement with the broader machine learning community.
- Conduct original research and develop proof‑of‑concept solutions where appropriate.
- Advise and mentor quantitative researchers on methodology, experimentation and research direction.
- Help guide future investments in research tooling, infrastructure and compute capabilities.
Qualifications
- PhD in Machine Learning, Computer Science, Statistics, Mathematics, Physics or a related quantitative discipline.
- Outstanding academic credentials and a strong publication record in leading research venues.
- Current or recent experience in a faculty‑equivalent academic or research leadership role such as Assistant Professor, Associate Professor, Professor, Group Leader, Principal Investigator, Senior Postdoctoral Researcher, or Senior Research Scientist.
- Deep expertise in modern machine learning and strong awareness of emerging research trends.
- Experience influencing research direction, mentoring researchers, or leading research initiatives.
- Strong programming skills and experience with modern machine learning frameworks.
- Excellent communication skills and the ability to collaborate across disciplines.
Eligibility
- Finance experience is not required.
Benefits
- Access to world‑class datasets, significant compute resources and a highly collaborative environment.
- Continued engagement with the academic community through conferences and publication opportunities.
- Competitive compensation that reflects scientific excellence and commercial impact.
Principal Research Scientist - Machine Learning in City of Westminster employer: IMC
As a Principal Research Scientist in Machine Learning at our company, you will thrive in a dynamic and collaborative environment that champions scientific excellence and innovation. With access to world-class datasets and significant compute resources, we foster a culture of mentorship and continuous learning, ensuring that your contributions not only advance your career but also make a meaningful impact in the field. Join us to engage with the academic community and lead pioneering research initiatives that shape the future of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Research Scientist - Machine Learning in City of Westminster
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like IMC!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Principal Research Scientist - Machine Learning at IMC.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like IMC.
✨Apply Directly through Our Website
When you find a suitable opening like Principal Research Scientist - Machine Learning at IMC, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Principal Research Scientist - Machine Learning in City of Westminster
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 IMC, 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 IMC. 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 IMC
✨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!
✨Showcase Your Projects
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 IMC!
✨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.
