Trading Data & AI Analyst
Salary not stated · Compare with UK Quantitative Analyst pay →
Why work for us?
A career at Janus Henderson is more than a job, it’s about investing in a brighter future together.
Our Mission at Janus Henderson is to help clients define and achieve superior financial outcomes through differentiated insights, disciplined investments, and world-class service. We will do this by protecting and growing our core business, amplifying our strengths and diversifying where we have the right.
Our Values are key to driving our success, and are at the heart of everything we do:
Clients Come First - Always | Execution Supersedes Intention | Together We Win | Diversity Improves Results | Truth Builds Trust
If our mission, values, and purpose align with your own, we would love to hear from you!
Your opportunity
We are looking for someone who is already deep into AI, not just familiar with it, to join our EMEA Equity Trading team. You will analyse trading data, automate desk outputs and build tools that seek to improve our processes. This is a technical role, not a trading role: you will learn the domain from one of the most experienced equity trading teams in the industry, but you need to arrive with genuine AI and data capability from day one.
If you are the kind of person who builds things before being asked, picks up new tools fast and is not satisfied with how things were done yesterday, this is worth reading on.
You will:
- Own the AI and automation agenda for the team. You will have the freedom to identify where AI tooling can replace manual processes, design the solution and build it. This is not a role where you execute someone else's backlog; you are expected to bring ideas, test them quickly and ship what works.
- Work directly with Traders and Portfolio Managers to understand how they consume data, where their pain points are and what would change their workflow. The tools you build will be used by the most senior investment professionals in the firm, so everything you deliver needs to be clear, well designed and grounded in how the desk actually operates.
- Analyse trading datasets using Python and AI tooling to surface trends, inefficiencies and opportunities. You will encounter execution analytics, Transaction Cost Analysis, Algo Wheel configuration, market microstructure and European regulatory requirements. You do not need to arrive as an expert in all of these, but you need to be comfortable working with complex, domain-specific data and learning fast.
- Modernise the desk's day-to-day outputs from a consumable content standpoint so they are automated, visually sharp and worthy of readership.
- Help the wider team build confidence with AI tooling. Run demos, share practical examples, explain what works and why. The goal is not just for you to stay current with new tools and techniques, but to bring the rest of the desk along so the whole team's capability rises, as well as your own.
- Contribute to the firm's wider community of AI practitioners, sharing what works on the desk, learning from other teams & experts and evolving best practice for AI adoption across the organisation.
What to expect when you join our firm
- Hybrid working and reasonable accommodations
- Generous Holiday policies
- Excellent Health and Wellbeing benefits including corporate membership to ClassPass
- Paid volunteer time to step away from your desk and into the community
- Support to grow through professional development courses, tuition/qualification reimbursement and more
- Maternal/paternal leave benefits and family services
- Complimentary subscription to Headspace – the mindfulness app
- All employee events including networking opportunities and social activities
- Lunch allowance for use within our subsidized onsite canteen
Must have skills
- A degree in a technical or quantitative discipline, or equivalent professional experience. No specific degree subject is required; capability and aptitude matter more than the title on the certificate.
- Python and AI-assisted development. You will write code with AI, not without it. Comfortable working alongside agents and AI coding tools (GitHub Copilot, Claude Code or similar) to build, debug and iterate. Enough engineering judgement to ensure what you produce is safe, reliable and fit for production use on the desk and in an enterprise environment.
- AI proficiency. Prompt engineering, LLM-assisted analysis, agentic workflows, tool orchestration. You should be the person your peers come to when they want to know what is possible.
- Numerically sharp. Comfortable working with large, complex datasets and spotting when outputs do not make sense. This role sits on a trading desk, therefore absent of coding you will need good communication skills and fluent with numbers.
- Delivery mindset. Builds things that work and last, whether handed to a technology team to productionise or owned and maintained on the desk.
- Stakeholder communication. Can explain technical trade-offs clearly to non-technical audiences.
- 2-3+ years in a technical, data or analytics environment. Financial services exposure is a plus, not a prerequisite.
Nice to have skills
- Demonstrated personal interest in AI beyond the workplace. Candidates who actively explore AI in their own time, whether through side projects, experimentation with new models, or automating real-world problems outside of work, tend to bring a level of curiosity and initiative that is difficult to teach. This will be explored during the interview process.
- Financial knowledge. Exposure to equity markets, trading, execution analytics, algorithmic trading or market microstructure. Interest in developing this knowledge (e.g. CFA study) is also valued.
- SQL and data platforms. Comfortable querying structured data, ideally with experience in Snowflake or similar cloud data warehouses.
- Data visualisation and design. Experience with dashboarding or visualisation tools (e.g. Streamlit, Power BI or similar). An eye for how information is presented to a senior audience.
- Platform-level automation. Experience with low-code/no-code platforms (e.g. n8n, Copilot Studio), MCP, LLM observability tools (e.g. Langfuse), or managed model APIs (Azure AI Foundry, OpenAI, Anthropic).
- Modern development practices. Familiarity with any of: Docker, Terraform, CI/CD pipelines, Git.
- Agent orchestration frameworks. Experience with LangChain, Semantic Kernel, AutoGen or similar is a plus. The team is moving towards more sophisticated agentic workflows.
Supervisory responsibilities
- No
Potential for growth
- Mentoring
- Leadership development programs
- Regular training
- Career development services
- Continuing education courses
You will be expected to understand the regulatory obligations of the firm, and abide by the regulated entity requirements and JHI policies applicable for your role.
At Janus Henderson Investors we’re committed to an inclusive and supportive environment. We believe diversity improves results and we welcome applications from candidates from all backgrounds. Don’t worry if you don’t think you tick every box, we still want to hear from you! We understand everyone has different commitments and while we can’t accommodate every flexible working request we’re happy to be asked about work flexibility and our hybrid working environment. If you need any reasonable accommodations during our recruitment process, please get in touch and let us know at recruiter@janushenderson.com
#LI-LN2 #LI-HYBRID
Annual Bonus Opportunity: Position may be eligible to receive an annual discretionary bonus award from the profit pool. The profit pool is funded based on Company profits. Individual bonuses are determined based on Company, department, team and individual performance.
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