Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quantitative Developer

Aurum Search Limited
Crawley
6 months ago
Applications closed

Related Jobs

View all jobs

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer (C#) - Up to 160k + Exceptional Bonus - Elite FinTech Firm- London - Hybrid Working

Quantitative Developer - eFX (Java)

Quantitative Developer - (Python | Equities | Backtesting) Key Skills: Python, Equities, Backtesting

Our client is a multi-strategy hedge fund manager dedicated to identifying and capitalising on market inefficiencies through a combination of discretionary and quantitative trading strategies.


We are looking for a Python Developer to collaborate directly with Quantitative Researchers and Software Developers to design, implement, and deploy software to retrieve, process, and present data efficiently. You will be leveraging modern development principles to ensure efficient and elegant solutions for data. You'll drive cross-team initiatives and work closely with technologists, quantitative researchers, and investment professionals across all asset classes to achieve our client's objectives.


Job Responsibilities:

  • Work with software developers and quantitative researchers to design and build efficient and scalable workflows for data processing and retrieval.
  • Collaborate closely with colleagues in technology to ensure consistency across our client in order to maximize the re-use of core software components.
  • Assist in building and maintaining automated solutions for our client's core data infrastructure, trade processing and reporting.
  • Assume strong ownership of projects throughout their full production deployment life cycle.
  • Improve documentation and procedures for end user, quant and development teams.
  • Meaningfully contribute to our client's overall data strategy.


Requirements:

  • 3+ years of experience with Python in a development role with a focus on data processing and analysis.
  • Experience in and proficiency with database and cloud technologies (e.g. MySQL, Google, BigQuery, etc).
  • Hands on individual that has the ability to work in a collaborative manner with other members of the firm.
  • Strong written/verbal communication, problem-solving and organizational skills.
  • Highly motivated and intellectually curious individual with a keen eye for automation.
  • Ability to manage multiple projects and tasks.
  • Well-organized, proactive, resourceful, able to handle a fast-paced environment, question the status quo, accountable and possesses an ownership mindset.
  • Experience in the financial industry is a plus but not an absolute requirement.

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.

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.