Senior Equity Quantitative Researcher

Deutsche Bank
Greater London
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Data Analyst

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Description

:

Job TitleSenior Equity Quantitative Researcher

LocationLondon

Corporate TitleVice President

As a senior equity quantitative researcher, you will join the Quantitative Investment Solutions (QIS) Research team at Deutsche Bank in London.

Your output will be presented in research reports, presentations, webinars and roadshows. The alphas you develop will also be implemented in the form of investable indices, which requires interacting with different implementation teams.

What we’ll offer you

A healthy, engaged and well-supported workforce are better equipped to do their best work and, more importantly, enjoy their lives inside and outside the workplace. That’s why we are committed to providing an environment with your development and wellbeing at its centre.

You can expect:

Hybrid Working - we understand that employee expectations and preferences are changing. We have implemented a model that enables eligible employees to work remotely for a part of their working time and reach a working pattern that works for them Competitive salary and non-contributory pension 30 days’ holiday plus bank holidays, with the option to purchase additional days Life Assurance and Private Healthcare for you and your family A range of flexible benefits including Retail Discounts, a Bike4Work scheme and Gym benefits The opportunity to support a wide ranging CSR programme + 2 days’ volunteering leave per year

Your key responsibilities

Carrying out independent cutting-edge research in equities, with a focus on fundamental (such as accounting related), alternative and market data aimed at launching systematic trading strategies. Monitoring and explaining the performance of a suite of factor strategies across the whole asset class to internal and external clients Evaluating and onboarding new datasets that better capture the changing nature of equity factors, as well as new factors

Your skills and experience

Previous relevant experience in finance, with a focus on equities. A background in company research or quantitative research is a plus Experience with Python, in particular using standard libraries such as Pandas and Numpy. Python will be a core part of your development environment Experience working with financial datasets of various kinds. Experience carrying out independent and original research Strong econometric and data science skills Excellent written, verbal and interpersonal communication skills Excellent problem-solving skills

How we’ll support you

Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs We value diversity and as an equal opportunities’ employer, we make reasonable adjustments for those with a disability such as the provision of assistive equipment if required (for example, screen readers, assistive hearing devices, adapted keyboards)

About us

is the leading German bank with strong European roots and a global network. Click to see what we do.

Deutsche Bank in the UK is proud to have been named in for five consecutive years. Additionally, we have been awarded a Gold Award from Stonewall and named in their for our work supporting LGBTQ+ inclusion.

We strive for a in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.

Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.

We welcome applications from all people and promote a positive, fair and inclusive work environment.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.