Product Manager, Analytics

Summary

The Product Manager, Analytics will be a credible, experienced product professional with excellent communication skills. They should have strong knowledge of margin and collateral analytics, with a focus on advanced optimisation, stress testing and forecasting analytics, and a keen interest in how clients use these tools across the derivatives trade lifecycle. They will decide what problem the Analytics team solves, for whom and why, collaborating closely with engineers, internal teams and clients.

The Analytics area covers margin optimisation, margin attribution, collateral analytics and optimisation, variation margin forecasting, stress testing and the limits engine.

The Product Manager, Analytics will report to the Head of Product.

Full Time – London

About us

Step into the future with Cassini — Founded in 2014, we are the established, core utility provider of analytics and optimization tools built for the derivatives industry. From London to New York, Sydney to Singapore, hedge funds, asset managers, and banks worldwide rely on our solutions.

Our award-winning platform empowers clients to reduce margin, optimize collateral, and enhance their liquidity risk framework, delivering real-time, front-to-back analytics on the full cost of derivatives trading.

What sets us apart?

Recognised as 'Best Derivatives Tech Provider' and 'Analytics Leader’

Global impact with a rapidly expanding footprint

Analytics provider to the largest asset managers in the world

Enterprise-grade security (ISO 27001 & SOC-2)

Seamless integration with OMS, EMS, and collateral systems

At Cassini, our client focus drives everything we do. We’re a collaborative, energetic team transforming how the financial world manages their liquidity risk. With challenging projects, continuous learning opportunities, and cutting-edge technology, we empower our employees to grow their skills and reach their full potential every day.

Role

Product:

Own the product roadmap for the Analytics area and decide the order of work within it.

Decide which problems the team solves, for which clients and why, and what is out of scope.

Write clear requirements for each feature: the problem, who has it and what success looks like.

Agree each specification with engineers, business analysts and test engineers before build starts, and confirm that the finished feature meets the original intent.

Explore new or unclear ideas using AI tools before they go to the engineering team.

Assess the commercial impact of each feature, and flag when a change creates a new module or changes an existing one.

Keep documentation of what the Analytics modules cover up to date.

Work with the Market Data team early to confirm the data that new features need.

Client-Facing:

Explain how the analytics modules behave, in plain words, to Relationship Managers, Sales and Support.

Hold a regular weekly slot for support questions, and help Support classify and resolve issues in the Analytics area.

Identify client challenges and translate them into potential future Cassini solutions.

Tech Stack

We work with an exciting, modern stack built for scale, reliability, and productivity. To be successful in this role, you’ll need solid experience with some of the core tools, platforms, and technologies we work with:

Jira, Confluence and the agile workflow

Figma, Lucid and other wireframing tools

Generative AI tools

A basic understanding of our technology stack is also helpful, although not essential:

SQL databases

AWS infrastructure

Python

APIs / SFTP

Required Qualifications, Skills & Experience;

A successful candidate will have the following:

Sound knowledge of collateral and margin analytics, including optimisation algorithms.

Experience with derivatives margin and collateral, such as SIMM, SPAN or clearing house margin (preferred).

Experience with AI-assisted development or specification-led delivery (preferred).

Working knowledge of Jira, Confluence and agile workflow.

Working knowledge of generative AI tools, including Claude and Cursor.

Working knowledge of APIs, databases and SFTPs.

Preferred Qualifications, Skills & Experience;

Experience of Repo, Stock Borrow Lend or other financing solutions

Understanding of margin models and optimisation algorithms

Knowledge of the buy-side or sell-side’s operating processes

Experience using and defining API endpoints

Good understanding of data modelling and experience defining new data models

Some Python or VBA coding experience

Demonstrable experience using AI tools to fast-track tasks, automate processes and solve problems