At a Glance
- Tasks: Develop innovative models and tools for parametric insurance in construction projects.
- Company: Exciting tech startup transforming construction with deep learning.
- Benefits: Competitive salary up to £95k, options, and remote work flexibility.
- Other info: Relaxed, open environment with autonomy and excellent career growth opportunities.
- Why this job: Make a real-world impact on major infrastructure projects while working with cutting-edge technology.
- Qualifications: PhD-level expertise in a technical field and strong skills in Python and statistics.
The predicted salary is between 85500 - 104500 £ per year.
Quant Analyst Modelling To 95k Plus Options Quant Capital is urgently looking for a Quant Analyst to join our high profile client.
Our client is a is a recently founded technology business that seeks to improve the way projects are delivered, using the power of deep learning.
They are funded by well known names in the PE space.
My client is all about making construction more predictable via a comprehensive understanding of plan outcomes, and a crucial part of that is being able to deliver deep insights for very large construction schedules.
They’re working on some of the largest infrastructure projects in the world, which means having the opportunity to have true impact on the world around us.
The environment is that of Facebook or Google, relaxed open with time to think and make the right decisions.
The atmosphere is calm and relaxed with an open dress code.
This is a role for techies, those who are motivated by the sharp end of technology and the possibility of making serious money doing something you are passionate about.
You will temporarily report to the Science Director, and work in very tight collaboration with our diverse technical teams, as well as the commercial team trying to create a completely new type of parametric insurance for projects.
You will have a lot of autonomy to create new tools and explore new strategies, so will have to be self-guided in the exploration of what’s possible.
You will be responsible for ensuring that our dataset is up to scratch for testing insurance strategies.
You will create and maintain parametric backtesters, strategy descriptions languages, pricing models, and any other tools that will be relevant to creating effective insurance products.
You will collaborate with the commercial team in defining the free parameters of commercial contracts and their boundaries, as well as working with insurer and reinsurer teams on the packaging of insurance portfolios.
Quant Analysts should have
- Strong mathematical and statistical skills
- Deep understanding of forecasting
- Ph D-level (or equivalent) in a technical discipline
- Understanding of how to create pricing strategies
- Understanding of how to backtest various strategies and measure their performance
- Specialised knowledge of insurance and/or options pricing or financial services
- Knowledge of extreme statistics
- Proficiency in Python and associated Data Science libraries and tools (pandas, numpy, seaborn, matplotlib, scipy) My client is based in the City of London but this is a Remote Role.
Quant Analyst Modelling in London employer: Quant Capital
Quant Capital is an excellent employer for those looking to thrive in the fintech sector, offering a vibrant work culture that fosters innovation and collaboration. With substantial training and development opportunities, employees can enhance their skills while enjoying a flexible hybrid work model in the heart of London. Join us to be part of a forward-thinking team that values growth and cutting-edge technology.
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We think this is how you could land Quant Analyst Modelling in London
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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 Quant Capital.
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We think you need these skills to ace Quant Analyst Modelling 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 Quant Capital, 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 Quant Capital. 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 Quant Capital
✨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 Quant Capital!
✨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.
