At a Glance
- Tasks: Collaborate with researchers and traders to enhance datasets for investment strategies.
- Company: Leading quantitative investment firm at the forefront of data-driven trading.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Ideal for those passionate about solving complex data challenges in finance.
- Why this job: Make a real impact on trading decisions by working with cutting-edge financial data.
- Qualifications: 3+ years in data science, strong Python skills, and knowledge of financial datasets.
The predicted salary is between 63000 - 77000 £ per year.
A leading quantitative investment firm is looking to hire multiple Data Scientists to join a highly visible front-office data function supporting researchers and trading teams across global markets.
This team sits at the intersection of data, research and trading, and is responsible for identifying, onboarding, validating and enhancing datasets that drive investment decisions.
- We are particularly interested in candidates with deep expertise in
- Fixed Income (ideally Rates) ,
- Pricing Data , or
Index Data , as the team is looking to add specialist knowledge across each of these areas.
- What You'll Be Doing
- Partnering with researchers and traders to understand data requirements and identify new opportunities.
- Sourcing, evaluating, onboarding and enhancing datasets used within systematic investment strategies.
- Building Python-based tooling and workflows to extract, clean, validate and transform data.
- Creating research-ready datasets, features and data products for front-office users.
- Assessing data quality, coverage, robustness and suitability for investment applications.
- Working closely with engineering teams to productionise and scale data solutions.
- What Makes This Role Different
This is not a pure modelling role and it is not a traditional data engineering position.
The strongest candidates tend to be people who enjoy understanding datasets end-to-end - where they come from, how they should be validated, what signal they contain, and ultimately how they can be leveraged by researchers and investment teams.
The team works across the full data lifecycle, from discovery and onboarding through to research application and production use.
Ideal Background
We're interested in candidates who combine strong technical skills, financial markets knowledge and genuine curiosity around data.
- Data Scientists, Quantitative Data Specialists, Data Engineers or Research Data professionals from hedge funds, asset managers, investment banks, proprietary trading firms or market data providers.
- Experience working with Fixed Income, Rates, Pricing, Reference, Index, Market or Alternative datasets.
- Strong Python experience and familiarity with modern data libraries and workflows.
- Exposure to quantitative research, systematic investing, pricing, portfolio analytics, risk, market data or data platform environments.
- Strong academic credentials in a quantitative discipline from a leading university.
- Key Requirements
- 3+ years of relevant industry experience.
- Advanced Python programming skills.
- Experience working with financial datasets in a research, trading, pricing, risk or market data context.
- Strong understanding of data quality, validation, transformation and production workflows.
- Excellent communication skills and the ability to work directly with both technical and business stakeholders.
- Ideal Profile
The team is particularly interested in candidates who combine
- Expertise in either Fixed Income (preferably Rates), Pricing Data or Index Data.
- Strong academic achievement from a leading university.
- Demonstrable ownership of complex data problems.
- Stable career progression and meaningful tenure within high-performing organisations.
- A genuine interest in financial markets and quantitative investing.
This opportunity is particularly well suited to individuals who enjoy solving complex data problems, working closely with investment teams, and building datasets and tooling that have a direct impact on research and trading outcomes.
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Data Scientist - Fixed Income, Pricing or Index Data employer: Selby Jennings
Selby Jennings is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of London. Employees benefit from extensive growth opportunities, competitive compensation, and a supportive environment that encourages professional development, making it an ideal place for those looking to make a meaningful impact in the finance technology sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist - Fixed Income, Pricing or Index Data
✨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 Selby Jennings!
✨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 Data Scientist - Fixed Income, Pricing or Index Data at Selby Jennings.
✨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 Selby Jennings.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist - Fixed Income, Pricing or Index Data at Selby Jennings, 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 Data Scientist - Fixed Income, Pricing or Index Data
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 Selby Jennings, 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 Selby Jennings. 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 Selby Jennings
✨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 Selby Jennings!
✨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.
