Quantitative Researcher New

Quantitative Researcher New

Full-Time 54000 - 66000 £ / year (est.) No working from home possible
Trading Interview

At a Glance

  • Tasks: Build models and strategies for pricing and trading financial instruments.
  • Company: Join a leading firm with a collaborative and innovative culture.
  • Benefits: Competitive salary, mentorship, and access to cutting-edge technology.
  • Other info: Dynamic environment with opportunities for growth and learning.
  • Why this job: Dive into data and make impactful contributions in finance.
  • Qualifications: Strong programming skills in Python and a curious mindset.

The predicted salary is between 54000 - 66000 £ per year.

We are looking for Quantitative Researchers to help us build models, strategies, and systems that price and trade financial instruments. You’ll work side by side with experienced researchers who are committed to teaching, guiding, and supporting our newest hires, learning how we think about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets.

At Jane Street, our researchers, engineers, and traders sit a few feet away from each other and work together to train models, architect systems, and run trading strategies. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing tens of thousands of high-end GPUs. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance, or studying how our model likes to trade in production.

We don’t believe in “one-size-fits-all” modelling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep learning, depending on what best fits a given problem. The most successful researchers will be driven by a curiosity for how their contributions fit into the larger picture of our trading operations, and how to adapt their findings into actionable strategies.

About You

If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in.

  • Able to apply logical and mathematical thinking to all kinds of problems
  • Intellectually curious; eager to ask questions, admit mistakes, and learn new things
  • A strong programmer who’s comfortable with Python
  • An open-minded thinker and precise communicator who enjoys collaborating with colleagues from a wide range of backgrounds and areas of expertise

Most candidates will have experience with data science or machine learning, but ultimately, we’re more interested in how you think and learn than what you currently know. PhD or other research experience is a plus.

We were founded by a small group of traders and technologists in a tiny New York office. Today, we have more than 2,000 employees across five global offices.

Quantitative Researcher New employer: Trading Interview

Tower Research Capital is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation and rigorous experimentation are at the forefront. Located in a vibrant financial hub, employees benefit from cutting-edge technology and resources, alongside ample opportunities for professional growth and development within the fast-paced world of quantitative trading. Join us to be part of a team that values your contributions and rewards your success in a meaningful way.

Trading Interview

Contact Details:

Trading Interview Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Quantitative Researcher New

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Apply Directly through Our Website

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We think you need these skills to ace Quantitative Researcher New

Model Building
Experiment Design
Dataset Generation
Time Series Analysis
Feature Engineering
Statistical Techniques
Machine Learning

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 Trading Interview, 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 Trading Interview. 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 Trading Interview

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 Trading Interview!

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.