Quantitative Financial Engineer

Sowelo Consulting sp. z o.o. sp. k.

Bristol, England

12 months ago

Applications closed

Related Jobs

View all jobs

Genomic Data Scientist in Rare Disease (we have office locations in Cambridge, Leeds & London)

Genomics England Canary Wharf, London, E14 5AB, United Kingdom

£55,000 – £100,000 pa

Anaplan Model Builder

Vallum Associates Reading, Berkshire, United Kingdom

£40,000 – £60,000 pa Hybrid

Senior Data Strategy Consultant, Marketing Solutions

TransUnion London, United Kingdom

KDB Developer

James Joseph Associates Broad Street, Greater London, City And County Of the City Of London, United Kingdom

£120,000 – £150,000 pa

Data Scientist

Randstad Technologies Recruitment London, United Kingdom

Senior Data Scientist

Faculty AI London, United Kingdom

£50,000 – £80,000 pa Hybrid

Posted: 3 May 2025 (12 months ago)

Save job

Create job alert

Applications closed

Are you a detail-oriented professional with a passion for Quantitative Finance and Advanced Engineering?

Have you excelled in building financial models or developing algorithmic trading systems?

If so, we have a remarkable opportunity for you! Based in the vibrant city of London, but with the flexibility of a global reach, our client is a leading entity specialized in FinTech solutions and pioneering technology.

We are seeking a highly skilled Quantitative Financial Engineer to join our dynamic team. This specialist will play a critical role in developing, optimizing, and scaling pricing models, execution algorithms, and API-based financial integrations across an extensive range of instruments, including Spot FX, Derivatives, Structured Products, and Futures.

Key Responsibilities

Spearhead the development and implementation of financial instruments, including CFDs, futures, structured products, and derivatives.
Design sophisticated pricing models and execution strategies to ensure competitive spreads and efficient price discovery.
Integrate prime brokers, market data, and liquidity providers into the platform to support diverse product portfolios.
Collaborate with trading desks and senior leadership to refine market offerings and optimize risk management.
Serve as the lead quantitative expert, troubleshooting execution and pricing anomalies in real-time.
Enhance trading infrastructure and oversee the automation of execution algorithms in cooperation with developers.
Build and backtest proprietary models, ensuring seamless integration into trading systems.
Develop quantitative tools for monitoring market microstructure, trading performance, and overall liquidity dynamics.

Required Qualifications

A minimum of 5 years’ experience in roles specializing in Spot FX, Derivatives (Futures, Options, Swaps), Structured Products, and CFDs.
Profound expertise in derivatives pricing techniques, quantitative risk models, and algorithmic execution strategies.
Fluency in yield curve modeling, stochastic pricing mechanisms, and volatility surface analyses.
Demonstrated experience in developing API-based pricing engines and understanding order book dynamics.
Background in financial institutions like banks, hedge funds, or brokers in quantitative roles.
Proficiency with real-time integration of pricing feeds and automation in quant-driven execution.
Advanced programming abilities, ideally in Python.
Strong command of English (both written and spoken).

Preferred Qualifications

Experience with advanced hedging algorithms and risk control frameworks.
Proven background in algorithmic trading system development and market microstructure analytics.

Keys to success:

Expertise in SpotFX

Joining us means you'll enjoy:

A fully remote work opportunity
Flexibility with either B2B or permanent contracts
Annual performance-based bonuses

Sounds interesting? Send us your CV by applying to this page!

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

Industry Insights

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

Apr 9, 2026

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Mar 24, 2026

Jobs

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.

Feb 10, 2026

Careers

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.