Product Manager - Algorithmic Trading

Product Manager will be responsible for developing valuable and viable products (& implicit services) that consider the voices of the business & commercial, trading & research, and the tech teams they work in. To listen to a user's voice, you should be able to speak their language. We call this trilingual-competency around the domains of Keyrock’s business considerations, industry context, and tech (consisting of Rust and JS/TS tooling, in a distributed global cloud architecture).

Product Managers do this by empowering product development teams to solve complex user and business problems, with effective user engagement and blistering tech performance. Keyrock product development teams (squads) are cross-functional, generally composed of a squad lead, a product manager, a development manager, and several engineers/tech-supports. Users are internal trading & research teams, and external clients. The Product is the Keyrock Liquidity Platform that executes trading strategies for users and facilitates Keyrock services for external clients.

Product Managers are expected to discover and deliver valuable product features and changes via user discovery & development of user insight with consideration for micro-targeted design that encourages user behaviour towards business objectives (e.g. risk), making changes more viable. Value is measured by the data-oriented product managers to hold empowered team teams accountable to deliver outcomes. This means team development capabilities are critical to the role, to ensure team cohesion and efficient communication.

Finally a Keyrock Product Manager will need to understand the difference between Product and Project mindsets and encourage the adoption of a Product view amongst the development teams.

Essential Competencies (At least 2 out of 3):

1. Exposure to quantitative analysis of financial assets, or econometrics, or statistical analysis of investments (or other relevant strong mathematical experience). For example, modelling trading strategies for short term trading, using statistical signals.

2. Exposure to business administration or strategic analysis experience that enables the candidate to own the business viability considerations of the product, such as risk, regulatory alignment, marketing considerations, and cost relative to organisational size - and to know what to ask to assess industry considerations.

3. Previous experience with software engineering, with enough knowledge to be able to understand technical constraints, cloud architecture, and network-related technical challenges when building a distributed trading system. The candidate should be able to participate in, and contribute to, engineering and architectural conversations.

Note: Whilst two out of three of the above may be accepted, the candidate should be able to demonstrate mastery of the two competencies they possess, with an idea of how they would look to develop the third.

Qualifications:

• Bachelor’s degree or equivalent practical experience with demonstrated capabilities transferable to this role

• Demonstrated understanding of the techniques and methods of modern product discovery and product delivery.

• 2 years working on technology-powered products as either a product manager, UX/product designer, engineer, data analyst, data scientist, or user researcher.

• Demonstrated ability to learn multiple functional areas of business – engineering, design, finance, sales, or marketing.

• Demonstrated ability to figure out solutions to hard problems with many constraints, using sound judgement to assess risks, and to lay out your argument in a well-structured, data-informed, written narrative.

• Proven ability to engage productively with engineers, designers, and company leaders in a constructive and collaborative relationship.

Nice to haves:

• Any Agile or related qualification around iterative software development and/or product management.

• Business strategy/marketing qualifications, or equivalent experience.

• Good understanding of the DeFi ecosystem or algorithmic trading