Partner with asset allocation PMs and researchers to take ideas from notebook to production: signals, CMAs, optimization, portfolio construction, rebalancing rules, and attribution.
Build and extend the team's research platform: data ingestion, back testing, scenario analysis, portfolio construction, monitoring, and reporting.
Own the multi-asset data layer: market data, macro, fundamentals, fund and index data, internal holdings, with quality control the PMs actually trust.
Use AI coding agents daily for prototyping, refactoring, testing, review, and documentation. Bring opinions on where they help and where they hurt.
Build internal AI-backed tooling for the team where it earns its keep: research workflows, client-reporting drafts, commentary support, meeting prep.
Write production code that other quants want to build on. Own reliability, testing, and observability for what you ship.
Mentor teammates on effective AI-augmented engineering practice.
Carry out other duties as assigned
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
Have built industrial-scale enterprise-quality quantitative/systematic models based on specs provided by PM's.
Have deployed quantitative/systematic models to production at non trivial size. Have monitored operational performance of these models and taken ownership of making sure the models behave properly
Are familiar with the SDLC (eg testing/deployment)
Are heavy users of modern AI tools (claude code/codex/opencode/pi/ampcode/factory droid/cursor/cline)
Have written extensive documentation about the implementation of a model.

Working knowledge of financial markets preferred
Knowledge of Excel preferred
Github (or other version control), CI/CD and/or cloud services experience is beneficial
Excellent interpersonal, relationship building and customer service skills
Strong econometrics and statistics background, experience in asset pricing empirical work
Passionate about financial markets with a curiosity about investing
No
Mentoring
Leadership development programs
Regular training
Career development services

A career at Janus Henderson is more than a job, it's about investing in a brighter future together.

82 Financial Services / Investment jobs in Dagenham, Greater London