Summary
Our Apprentice programme starts in September 2025, you will join our Quantitative Strategies and Data Group, within Global Markets, working in a full-time role whilst studying with one of our trusted learning providers, graduating after three years with a BSc (Hons) in Data Science.
Wage
Competitive
Training course
Data scientist (integrated degree) (level 6)
Hours
Monday to Friday, 9am to 5pm (additional hours may be required)
35 hours a week
Possible start date
Monday 8 September
Duration
3 years
Positions available
1
Work
As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.
What you’ll do at work
Quantitative Strategies and Data Group (QSDG) uses models, data, and analytics to develop and deliver impactful solutions to sales and trading teams across Global Markets. We collaborate across business lines and are guided by the highest standards of governance, ethics and scientific rigor. In your role you will contribute directly to the firm by helping us serve our clients and manage risk. You will be on active projects in the fast-paced environment of the trading floor.
As an apprentice, your key tasks and responsibilities may include but are not limited to:
* Applying statistical and data science techniques to analyse market dynamics and client behaviour.
* Participate in the development of models and strategies that the business use to make trading decisions.
* Studying, implementing, and improving electronic trading algorithms.
* Building signals and tools to improve the efficiency and profitability of the trading business.
* Contribute to the development of pricing models to understand and manage the risks of complex derivative products
Where you’ll work
2 King Edward Street
London
EC1A 1HQ
Training
An apprenticeship includes regular training with a college or other training organisation. At least 20% of your working hours will be spent training or studying.
College or training organisation
BPP UNIVERSITY LIMITED
Your training course
Data scientist (integrated degree) (level 6)
Equal to degree
Course contents
* Identify and clarify problems an organisation faces, and reformulate them into Data Science problems. Devise solutions and make decisions in context by seeking feedback from stakeholders. Apply scientific methods through experiment design, measurement, hypothesis testing and delivery of results. Collaborate with colleagues to gather requirements.
* Perform data engineering: create and handle datasets for analysis. Use tools and techniques to source, access, explore, profile, pipeline, combine, transform and store data, and apply governance (quality control, security, privacy) to data.
* Identify and use an appropriate range of programming languages and tools for data manipulation, analysis, visualisation, and system integration. Select appropriate data structures and algorithms for the problem. Develop reproducible analysis and robust code, working in accordance with software development standards, including security, accessibility, code quality and version control.
* Use analysis and models to inform and improve organisational outcomes, building models and validating results with statistical testing: perform statistical analysis, correlation vs causation, feature selection and engineering, machine learning, optimisation, and simulations, using the appropriate techniques for the problem.
* Implement data solutions, using relevant software engineering architectures and design patterns. Evaluate Cloud vs. on-premise deployment. Determine the implicit and explicit value of data. Assess value for money and Return on Investment. Scale a system up/out. Evaluate emerging trends and new approaches. Compare the pros and cons of software applications and techniques.
* Find, present, communicate and disseminate outputs effectively and with high impact through creative storytelling, tailoring the message for the audience. Use the best medium for each audience, such as technical writing, reporting and dashboards. Visualise data to tell compelling and actionable narratives. Make recommendations to decision makers to contribute towards the achievement of organisation goals.
* Develop and maintain collaborative relationships at strategic and operational levels, using methods of organisational empathy (human, organisation and technical) and build relationships through active listening and trust development.
* Use project delivery techniques and tools appropriate to their Data Science project and organisation. Plan, organise and manage resources to successfully run a small Data Science project, achieve organisational goals and enable effective change.
Your training plan
* Data scientist (integrated degree) Apprenticeship Standard
Requirements
Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.
Skills
* Communication skills
* IT skills
* Attention to detail
* Organisation skills
* Problem solving skills
* Presentation skills
* Number skills
* Analytical skills
* Logical
* Team working
* Non judgemental
* Patience