SCIB Associate, Quantitative Analyst

Santander UK
London
2 days ago
Create job alert

This job is with Santander UK, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

SCIB Associate, Quantitative Analyst

Country: United Kingdom

Business area introduction
The Front Office Quant area is in charge of the development of the pricing and risk models, as well as the pricing tools for Sales and trading teams. As part of the "Linear Rates, Inflation and Pricing tools" the focus of this position will be on the development of the pricing libraries for interest rates and inflation models as well as the curves library.
Key activities
Contribute to the design, implementation and maintenance of the curves library, both in mathematical modelling and implementation ( C++ and Rust languages )
Development of an efficient risk framework to represent the risks properly making usage of advance techniques (e.g. AD)
Extend further the bonds analytics to do RV analytics, z-score, correlations, carry and roll down, historical analysis, hedging strategies
Contribute to the model development of the linear rates products.
Design and extension of the APIs for our pricing and curves libraries.
Development and optimization of algorithms.
Refine existing quants framework and quantitative tools to meet highest quality standards.
Development, improvement, and maintenance of the testing process in our quantitative. libraries and tools.
Provide mathematical and technical documentation to internal stakeholders.
Keep up to date with mathematical and tech.
Support to Trading, Sales and Risk areas.
What we're looking for
Proficiency programming skills C++ and Python.
Knowledgeable in optimization techniques and numerical methods.
Good Knowledge of fixed income products and valuation.
Creative thinker, independently worker and capable to make decisions quickly, often under pressure and with limited information.
An excellent problem solver who can contribute with innovative ideas.
Strong interpersonal skills and a desire to work in a team environment are critical.
Higher qualification in Computer Science, Engineering, Mathematics, Physics or relevant mathematical based degree
Good programming skills in Rust.
Experience in curves construction and Adjoint risk or alternative techniques desirable.
Basic knowledge of options pricing theory, quantitative models, probability theory and stochastic processes.
What else you need to know
This role is based in our Triton Square office in London, conveniently located within walking distance from Euston Station and Warren Street Station.
How we'll reward you
As well as a competitive salary, you'll enjoy a benefits package that you can tailor to your needs.
Eligible for a discretionary performance-related annual bonus
Pension with generous contributions of up to 12.5% from Santander, depending on your own contribution and length of employment with us
27 days holiday plus bank holidays, with the option to purchase up to 5 contractual days per year
Company funded individual private medical insurance
Voluntary healthcare benefits at discounted rates such as private medical insurance for your family, dental insurance, healthcare cash plan and health assessments
Benefits supporting you and your family, such as death-in-service benefit, income protection, and voluntary life assurance and critical illness cover
Share in Santander's success by investing in our Sharesave and Partnership shares plans
For more information about our wide range of benefits and family friendly policies visit our website.
Equal Opportunities
Santander are an equal opportunities employer. When we talk about diversity, we don't just want to pay lip service. Our customers come from a wide range of backgrounds, and so do our people. It's important to us that we create an inclusive culture where everyone counts, and we particularly welcome applications from different underrepresented groups.
For more information on our commitment to equal opportunities, please visit our diversity page.
What to do next
If this sounds like a role you're interested in, then please apply on the link.
Due to high volume of applications we may need to close this role earlier than the advertised date, so recommend submitting an application as soon as possible.
#LI-DNI

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.

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.