At a Glance
- Tasks: Build ML-driven insight systems using financial time series data.
- Company: Data-driven fintech firm in London with a focus on innovation.
- Benefits: Competitive salary up to £200,000, equity, and direct impact on investor decisions.
- Other info: In-office role with opportunities for professional growth.
- Why this job: Join a dynamic team and influence real-world investor outcomes.
- Qualifications: Strong Python skills and 5+ years in quantitative analysis or financial modeling.
The predicted salary is between 110000 - 200000 £ per year.
A data-driven financial technology firm in London seeks a Quantitative Analyst to build ML-driven insight systems using structured financial time series data. This role requires strong Python skills and over 5 years of experience in quantitative analysis or financial modeling.
You will develop models, deploy them into production, and evaluate signals based on real-world investor outcomes.
The compensation ranges from £110,000 to £200,000 depending on experience, with equity included. This is an in-office role that offers direct influence on investor decision-making.
Senior ML Quant Engineer: Time-Series Signals (London) employer: Reflexivity
Join a leading data-driven financial technology firm in London, where innovation meets opportunity. With a strong emphasis on employee growth and a collaborative work culture, we offer competitive compensation packages, including equity, and the chance to make a tangible impact on investor decision-making. Our commitment to fostering talent ensures that you will thrive in an environment that values your expertise and encourages continuous learning.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Quant Engineer: Time-Series Signals (London)
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and tech sectors, especially those who work with ML and time-series data. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects and any models you've built. This is your chance to demonstrate your quantitative analysis prowess and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and real-world applications of ML in finance. We want you to be ready to discuss how your work can influence investor decisions directly.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior ML Quant Engineer: Time-Series Signals (London)
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your Python expertise in your application. We want to see how you've used it in past projects, especially in quantitative analysis or financial modelling. Don't just say you're good at it; give us examples!
Quantitative Analysis Experience is Key:Since we're looking for someone with over 5 years of experience, be sure to detail your relevant work history. We love seeing how you've tackled complex problems and what impact your work has had on investor outcomes.
Tailor Your Application:Take a moment to customise your application for this role. Mention specific projects or experiences that align with building ML-driven insight systems. We appreciate when candidates take the time to connect their background to what we do!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Reflexivity
✨Know Your Python Inside Out
Since this role requires strong Python skills, make sure you brush up on your coding abilities. Be prepared to discuss specific libraries and frameworks you've used in your projects, especially those related to machine learning and data analysis.
✨Showcase Your Quantitative Analysis Experience
With over 5 years of experience needed, highlight your past roles where you've successfully built financial models or conducted quantitative analysis. Bring examples of how your work has directly influenced decision-making in a financial context.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of time-series data and machine learning concepts. Practise explaining complex ideas clearly and concisely, as you'll need to demonstrate your ability to communicate effectively with both technical and non-technical stakeholders.
✨Demonstrate Your Problem-Solving Skills
Be ready to tackle hypothetical scenarios or case studies during the interview. Show how you approach problem-solving, from identifying the issue to implementing a solution, particularly in the context of financial modelling and investor outcomes.
