Technical PMO Analyst

Tower Research Capital is a leading quantitative trading firm founded in 1998. Tower has built its business on a high-performance platform and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.
Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.
Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.
At Tower, every employee plays a role in our success. Our Business Support teams are essential to building and maintaining the platform that powers everything we do — combining market access, data, compute, and research infrastructure with risk management, compliance, and a full suite of business services. Our Business Support teams enable our trading and engineering teams to perform at their best.
At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential. This team is responsible for driving firm-wide initiatives that require planning, coordination, and technical delivery across all groups including Core Engineering, Trading, Risk Management, Compliance, Finance and Operations.
The Role
We are hiring a technical PMO analyst part of our Platform Strategy and Transformation team to strengthen our PMO capability based in London. This is a hands-on, hybrid role: part project delivery and PMO operations, part builder of internal tools and metrics, and part owner of internal documentation quality.
You will help run the PMO day to day, collect and challenge project updates, define and build useful metrics/dashboards, and take ownership of selected projects. You will also write Python (with AI coding assistants) to automate work and ship small internal UIs/admin tools, and act as content manager for PMO and project documentation on Confluence (and related internal spaces).
This role suits someone who likes structure and delivery, can code enough to build practical tools, cares about clear documentation, and wants to grow into broader project management over time.
Responsibilities
PMO operations, metrics and reporting
Collecting, challenging, and consolidating project updates from project managers and delivery leads into clear, decision-ready status reporting.
Defining, building, and maintaining project and portfolio metrics (progress, delivery health, risks/issues, dependencies, milestones, capacity, and KPI trends).
Building and maintaining dashboards and management information used by leadership and project managers.
Supporting portfolio and programme forums: preparing materials, tracking actions, and following up to closure.
Maintaining RAID logs and helping keep project data accurate and up to date.
Tooling and automation
Writing Python scripts and small applications to support PMO workflows, including data collection, reporting, and automation across Jira and Confluence.
Automating repetitive workflows across Jira and Confluence (status collection, reporting, page and template updates, notifications).
Building small internal UIs and admin tools with AI coding assistants — practical PMO / project-management utilities rather than production trading systems.
Improve and extend internal PMO / project-management tooling over time (dashboards, trackers, lightweight apps).
Documentation and Standards
Acting as content manager for internal PMO and project documentation: structuring Confluence spaces/pages, maintaining quality and freshness, and retiring outdated content.
Creating and curating playbooks, project templates, training materials, and how-to guides so teams can self-serve.
Continuously improving PMO tooling, documentation standards, and ways of working — lighter process where possible, stronger visibility where it matters.
Project Delivery
Taking ownership of selected small-to-medium projects as Project Manager (scope, plan, stakeholders, risks, delivery, and communication).
Coordinating across engineering, business, and operations stakeholders to keep work unblocked and on track.
Qualifications
1–3 years of relevant experience in PMO, project coordination, junior project management, business analysis, operations tooling, or a similar delivery-support role (financial services, technology, or consulting preferred but not required).
Ability to code in Python for practical automation and data work (scripts, APIs, data cleaning/transformation, and basic applications); professional software-engineering background is not required.
Comfort building small UIs / internal tools with AI coding assistance (e.g. simple web interfaces, forms, dashboards, or admin utilities).
Ability to define and build metrics — turning project activity into clear indicators, charts, and actionable reporting
Strong written communication and editorial judgment, with the ability to act as content manager for internal documentation (structure, clarity, consistency, and upkeep).
Hands-on experience with Jira and Confluence Strong organisational skills and attention to detail; able to manage multiple work streams without dropping follow-ups.
Clear verbal communication skills; able to turn messy updates into concise reporting Ability to pivot tasks quickly with the evolving needs of the business and to navigate ambiguous environments while maintaining focus and delivering results.
Ability to support working across multiple time zones, as needed.
Proactive, ownership-oriented mindset; comfortable asking questions, challenging gently, and driving work to completion.
Nice to have: dashboarding / BI tools (Looker, Power BI, Tableau, Streamlit, Gradio, or similar); front-end basics or Python UI frameworks; Jira/Confluence API automation; Agile delivery exposure; prior end-to-end ownership of a small project or workstream; Confluence information architecture or training programme experience; interest in trading or fintech environments.
and independent trading teams. We have a 25+ year track record of innovation and a reputation for discovering unique market opportunities.
Tower is home to some of the world’s best systematic trading and engineering talent. We empower portfolio managers to build their teams and strategies independently while providing the economies of scale that come from a large, global organization.
Engineers thrive at Tower while developing electronic trading infrastructure at a world class level. Our engineers solve challenging problems in the realms of low-latency programming, FPGA technology, hardware acceleration and machine learning. Our ongoing investment in top engineering talent and technology ensures our platform remains unmatched in terms of functionality, scalability and performance.
At Tower, employees will find a stimulating, results-oriented environment where highly intelligent and motivated colleagues inspire each other to reach their greatest potential.
Tower Research Capital seeks a Quantitative Developer to join the Core Engineering team to help build out our Quantitative Execution Services. You will be closely working with researchers and traders on the Central Execution Desk, directly contributing to scale up Tower's Mid-Frequency Trading capabilities. This role sits at the intersection of research and engineering—ideal for someone who has prior experience with execution algorithms and quantitative trading systems, and can translate research ideas into robust, high‑performance production software.
Responsibilities
Design, implement, and maintain high performance services in Rust and Python for our execution desk, including algo wheel, smart order routers, internalisers, etc.
Partner closely with our quantitative researchers to take research prototypes to production: refactoring, adding tests, telemetry, SLIs/SLOs, and CI/CD automation.
Write robust pipelines for market‑data ingestion, model training/inference, and post‑trade analytics.
Optimize for reliability and performance (throughput, tail‑latency, memory footprint) on distributed systems running in production trading environments.
Establish best practices in code quality, observability, and on‑call readiness; write clear documentation to enable effective collaboration across research and engineering.
Qualifications