Data Scientist and Developer

TriVictus Capital
London
2 days ago
Create job alert

The Role

We are seeking a talented individual to join our Data Science and Development team. The team is responsible for supporting our investment process through the development of analytical tools and research into strategy ideas. The ideal candidate is pragmatic and passionate about the application of data science methodologies to finance and thrives in a small collaborative environment.

Responsibilities:

·      Support the research, development, and maintenance of quantitative and discretionary trading strategies.

·      Collect, clean, validate, and maintain financial, market, and alternative datasets

·      Build and maintain data pipelines for ingesting, transforming, and storing structured and unstructured data.

·      Assist in exploratory data analysis to identify patterns, signals, and anomalies in market data.

·      Implement research ideas into production-quality code the under guidance of senior team members.

·      Develop and maintain back testing and performance analysis tools.

·      Monitor data quality, model outputs, and trading systems; investigate and resolve issues as they arise.

·      Create tools and dashboards to support portfolio managers, traders, and researchers.

·      Optimize existing code for reliability, performance, and scalability.

·      Document code, data processes, and research methodologies to ensure transparency and reproducibility.

·      Contribute to risk analysis, reporting, and post-trade analytics.

·      Assist with integrating third-party data vendors, APIs, and execution systems.

·       Stay current with relevant developments in data science, quantitative finance, and financial markets

 

The ideal candidate:

·      2+ years exp in data science, quantitative research, or related discipline

·      Advanced knowledge of Python, SQL, or other programming languages

·      Proven experience in conducting quantitative analysis

·      Knowledge of financial asset classes such as equity, futures, and fixed Income

·      Attention to detail and strong communication skills

·      Master’s or PhD degree in a quantitative field such as data science, statistics, computer science or financial engineering

·      Experience in designing, building and testing systematic signals would be a bonus.

 

 

Related Jobs

View all jobs

Data Scientist – Advanced Analytics

Data Scientist

Lead Data Scientist

Data Scientist/Developer

Data Scientist/Developer

Senior Data Scientist, Game Analytics - Drive Player Insights

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 an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

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

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.