At a Glance
- Tasks: Develop and evaluate systematic investment strategies using cutting-edge technology.
- Company: Join AllianceBernstein, a leader in systematic fixed income investment.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on continuous learning and development.
- Why this job: Make an impact in finance with innovative strategies and advanced research tools.
- Qualifications: Advanced degree in relevant fields and strong Python programming skills required.
The predicted salary is between 60000 - 80000 £ per year.
AllianceBernstein’s Systematic Fixed Income team develops and manages cutting‑edge, high‑performance, fully systematic, factor‑driven fixed‑income portfolios.
We are seeking a quantitative researcher focused on systematic fixed‑income and credit strategies to join our London office. The successful candidate will collaborate with colleagues across the investment process and contribute to the development, implementation, and management of systematic strategies within AllianceBernstein’s Fixed Income division.
Responsibilities Include, but are not limited to:
- Developing and evaluating systematic investment strategies through simulations, backtesting, and strategy analysis.
- Working on portfolio optimization, data science, and quantitative research problems.
- Conducting factor discovery, factor return analysis, and risk attribution.
- Contributing to our quantitative research environment, abAlphaLabs, a Python‑based research platform.
- Taking a hands‑on role in the management and ongoing enhancement of systematic fixed‑income strategies.
What We’re Looking For:
- An advanced degree in Finance, Financial Engineering, Mathematics, Computer Science, Operations Research, Economics, Electrical Engineering, or a related field.
- Strong Python programming skills and deep familiarity with the Python ecosystem.
- Experience working with SQL databases.
- Excellent attention to detail, a strong focus on quality, and the ability to take ownership of projects.
- Knowledge of fixed‑income securities and markets, which is preferred but not required.
- Deep desire to understand and outperform the markets.
- Data science and machine learning skills are a strong plus.
- Exposure to modern development and operations tools, such as Airflow, Kubernetes, or similar technologies, is a plus.
Prior fixed‑income trading or portfolio management experience is not required.
London, UK
AVP/Quantitative Researcher employer: AllianceBernstein
AllianceBernstein is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets collaboration. Employees benefit from a culture that prioritises professional growth, with access to cutting-edge tools and resources like abAlphaLabs, fostering a strong focus on quantitative research and systematic strategies. The company values diversity and encourages a hands-on approach, making it an ideal place for those looking to make a meaningful impact in the finance sector.
StudySmarter Expert Advice🤫
We think this is how you could land AVP/Quantitative Researcher
✨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 AllianceBernstein!
✨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 AVP/Quantitative Researcher at AllianceBernstein.
✨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 AllianceBernstein.
✨Apply Directly through Our Website
When you find a suitable opening like AVP/Quantitative Researcher at AllianceBernstein, 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 AVP/Quantitative Researcher
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 AllianceBernstein, 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 AllianceBernstein. 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 AllianceBernstein
✨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 AllianceBernstein!
✨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.
