Quantitative Analytics Part Time Analyst 2025 Prague

Purpose of the role

To participate in the day-to-day operations of the Quantitative Analytics (QA) group by providing analytical insights and expertise that will help our business leaders and stakeholders make informed decisions, support existing trading strategies, develop new products, strategies and services, as well as identify new market opportunities building an understanding of the various models, products and technologies associated with the full scope businesses QA services sector

Accountabilities

• Application of the latest quantitative techniques to solve business problems, including research, development, and implementation of new models and solutions.
• Collaboration with cross-functional teams to support business initiatives. Collaborate with cross-functional teams and senior management to progress business initiatives.
• Participation in training and development programs to enhance skills and knowledge, conducting research to support strategic decision making, prepare presentations and reports to communicate research findings, and collaborate with senior management to implement research findings.
• Design, development and support of the quantitative research framework using C++, Python and other in-house domain specific languages.
• Participation in training to enhance analytical skill, programming knowledge, and understanding of mathematical concepts.
• Participation in technical design and development of the global team’s quantitative research systems, research notebooks and products.
• Training and mentoring of junior colleagues, facilitation of individual or group training sessions, and development and maintenance of training materials.

Analyst Expectations

• Execute work requirements as identified in processes and procedures, collaborating with and impacting on the work of closely related teams.
• Check work of colleagues within team to meet internal and stakeholder requirements.
• Provide specialist advice and support pertaining to own work area.
• Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
• Maintain and continually build an understanding of how all teams in area contribute to the objectives of the broader sub-function, delivering impact on the work of collaborating teams.
• Continually develop awareness of the underlying principles and concepts on which the work within the area of responsibility is based, building upon administrative / operational expertise.
• Make judgements based on practise and previous experience.
• Assess the validity and applicability of previous or similar experiences and evaluate options under circumstances that are not covered by procedures.
• Communicate sensitive or difficult information to customers in areas related specifically to customer advice or day to day administrative requirements.
• Build relationships with stakeholders/ customers to identify and address their needs.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join us as a part time student developer and discover the world of Barclays. Dive into our culture, engaging in real projects that offer a comprehensive business overview. In your business area, you'll receive an in-depth introduction, taking on immediate responsibility guided by a mentor and line manager. Forge connections, explore new horizons, and unlock growth opportunities. Join us during your penultimate year of university to build skills, expand knowledge, and embark on an impactful path towards a promising career.

Why the Quantitative Analytics Part Time Student Programme?

Our industry-leading group provides model development, analytics, and valuable quantitative advice to businesses across the bank. Applying to our programme? Means the opportunity to join one of our specialist teams, including:

Markets Quants 

Consisting of specialised modellers and developers, the team directly supports the Capital Markets division of the bank. Team members are responsible for researching, innovating, developing, testing, implementing, and supporting all quantitative models used for front-office pricing, valuation adjustments, along with market and counter-party credit risk management across all asset classes. Joining a group that partners with trading, structuring, and risk management functions across the bank, you’ll gain broad exposure to a variety of classic and contemporary financial engineering modelling techniques and markets instruments to help drive business strategy.

Statistical Modelling Quants
 
Comprised of data scientists, developers, data engineers, and researchers, the team directly supports the Finance, Treasury, Fraud Surveillance, Stress Testing, Climate Risk, as well as the Wholesale and Retail Credit Risk/Market Risk operations within the bank. Team members deliver solutions to develop, test, implement, and support all statistical and econometrics models for the estimation of default probabilities, recovery rates, exposures at default, forecasting models for net revenue, balance sheet projections, scenario generation/expansion, operational risk, climate change, economic capital models, and machine learning models for fraud detection, all while using the latest model development approaches and advancements in technology.

The chance to make an impact

As a Quantitative Analytics part time student developer, you'll be imersed in a dynamic and invigorating environemnt that exposes you to real-world challenges. Throughout your programme, you'll have the unique chance to apply cutting-edge quantitative techniques to solve practical business problems.
Your role will involve conducting research, devising and implementing new models and finding innovative technological solutions to enhace our computing and data infrastructure. 

The experience will give you an inside look into the daily responsibilities of a quant, as you continue to meeting the advanced modelling needs of a top-tier multinational banking operations. 

Collaborating with diverse stakeholders across various bank functions and locations will further enrich your journey. 

Quantitative Analytics at Barclays

Barclays Quantitative Analytics team is a global organisation of highly specialised modellers and developers responsible for researching, innovating, developing, testing, implementing, and supporting all quantitative models used for valuation and risk management across all asset classes.

What we're looking for

To be considered for this programme,  you must be motivated and curious and  have completed or be within your final 2 years of an undergraduate or postgraduate qualification, or equivalent, in a technical discipline such as Physics, Mathematics, Quantitative Finance, Economics, Statistics, Calculus, Computer Science, or other (Science, Technology, Engineering and Mathematics) STEM subjects. 

Ideally, you'll have mathematical and programming skills (ideally in C/C++, or Python) along with a knack for logical thinking and creative problem solving. You'll be a good communicator and team player.

Barclays Europe

We’ve had a presence in Europe almost as long as there’s been a Barclays. So, we’re building on solid foundations, leveraging our embedded talent, in 10 locations across the region allowing us to draw on a wealth of local and regional insight.

Working in Prague

Prague is our technology hub: a globally connected, strategically important centre of technological excellence where a collaborative community of around 1400 talented colleagues bring agile innovations to a wide range of customers.

It is the policy of Barclays to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, creed, religion, national origin, alienage or citizenship status, age, sex, sexual orientation, gender identity or expression, marital or domestic/civil partnership status, disability, protected veteran status, genetic information, or any other basis protected by law.