At a Glance
- Tasks: Transform complex financial data into actionable insights using NLP and AI techniques.
- Company: Join a leading financial markets intelligence firm with a focus on innovation.
- Benefits: Competitive salary, performance bonuses, and flexible remote work options.
- Other info: Exciting opportunity for career growth in a dynamic, data-driven environment.
- Why this job: Make a real impact in finance by leveraging cutting-edge technology and data science.
- Qualifications: 5+ years in quantitative analysis with strong NLP and AI skills required.
The predicted salary is between 63000 - 77000 £ per year.
Location: Fully remote or hybrid in London
Reports to: Head of Enterprise Sales
Employment type: Full-time, permanent
Compensation: Competitive, dependent on experience (base + bonus)
About the Role
Our client is seeking an experienced Quantitative Analyst with strong NLP and AI expertise to build the first in-house quantitative capability within an established financial markets intelligence and data business. This is a highly data-driven role at the intersection of quantitative finance, Natural Language Processing (NLP), machine learning and AI. A key focus will be applying modern NLP and AI techniques to proprietary, unstructured and semi-structured financial information, transforming text-rich datasets into structured intelligence, predictive signals and commercially valuable data products. The successful candidate will combine rigorous quantitative and statistical skills with practical experience using NLP, machine learning and AI/LLM approaches to extract insight from complex financial content.
Skills & Experience
- 5+ years’ experience in quantitative research, quantitative analysis or financial data science, ideally within a hedge fund, investment bank or similar financial markets environment.
- Alternatively, relevant experience within a fintech, financial-data or AI business.
- Proven experience deriving actionable or tradable signals from unstructured or semi-structured financial data.
- Strong practical experience in Natural Language Processing (NLP), machine learning and AI, particularly applied to text-based or alternative datasets.
- Experience with sentiment analysis, information extraction, text classification and/or LLM-based approaches to analysing financial information.
- Strong knowledge of statistical modelling, econometrics and time-series analysis.
- Strong programming skills, with Python preferred.
- Understanding of back-testing, statistical significance and out-of-sample validation.
- Experience with financial markets data; macro, fixed income, FX, commodities or credit experience is particularly relevant.
- Strong quantitative academic background, ideally mathematics, statistics, physics, computer science, engineering or econometrics.
- Ability to communicate complex quantitative, NLP and AI methodologies to both technical and commercial audiences.
Key Responsibilities
- Analyse proprietary historical and unstructured datasets to identify correlations with asset prices and potential tradable or predictive signals.
- Apply NLP and AI techniques to extract, classify and quantify information contained within large volumes of text-based financial content.
- Use machine learning, sentiment analysis and LLM/AI approaches to transform unstructured information into structured, machine-readable signals and analytics.
- Apply statistical and econometric techniques including time-series analysis, regression, cointegration and signal validation.
- Explore how modern AI and NLP methodologies can enhance existing datasets and create new quantitative data products and signals.
- Develop robust back-testing and out-of-sample validation frameworks.
- Improve the machine-readability, metadata and governance of proprietary datasets.
- Build reproducible research pipelines and establish quantitative data standards and best practices.
- Translate quantitative, NLP and AI research into commercial, client-facing datasets, signals and analytics products.
- Author technical research and white papers demonstrating methodologies, AI/NLP applications and findings.
Quantitative Analyst employer: TrueNorth®
TrueNorth® is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the financial markets intelligence sector. With flexible remote or hybrid working options available in London, employees benefit from a supportive environment that prioritises professional growth and collaboration, alongside opportunities to develop cutting-edge quantitative capabilities. Join us to be part of a forward-thinking team where your expertise in Python and quantitative research will be valued and rewarded.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Analyst
✨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 TrueNorth®!
✨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 Quantitative Analyst at TrueNorth®.
✨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 TrueNorth®.
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We think you need these skills to ace Quantitative Analyst
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 TrueNorth®, 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 TrueNorth®. 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 TrueNorth®
✨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 TrueNorth®!
✨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.
