Neptune North
Systematic Data Technologist
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Systematic Data Technologist
Who We Are
Neptune North was founded in 2024 as a joint venture between Oliver Wyman, a global leader in management consulting and part of the NYSE-listed Marsh, and Rokos Capital Management, a global alternative investment fund manager. Our people are exceptional technical experts, who thrive on exploiting leading-edge technologies to solve the most complex problems.
We provide bespoke technology solutions to businesses operating in the banking and financial services, private capital and defence industries.
Our working environment is founded on principles of trust, collaboration and shared purpose. We pride ourselves both on the high calibre of our people, and on the supportive workplace they create, where each individual is given autonomy to grow and thrive.
From our headquarters in Newcastle upon Tyne, UK, we operate across our international office network. We are expanding rapidly, building teams in key markets to stay close to our clients and talent.
Our Culture
We are looking for exceptional talent with excellent communication skills
- Collaboration is key, both internally and with our clients. We believe we do our best work when we are together and working hand in hand with business users
- Curiosity is something we embrace and value highly
- We want people who are positive and passionate, have proven problem solving capabilities, can work quickly to find solutions to complex challenges and unlock big opportunities
- People need to be able to take ownership and be trusted to deliver, going the extra mile
- We want people who are highly motivated and have a high desire to learn
Systematic Technology Team
Our client’s Systematic Tech team is responsible for building, maintaining, and supporting the core technology platform that underpins systematic research, trading, and production operations.
The team owns four core areas of the systematic platform: backtesting and research tools; runtime and execution pipelines for production trading; development infrastructure, including CI/CD, deployment, and monitoring; and production support for live systematic workflows.
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The team works closely with researchers, portfolio managers, and central platform teams to ensure the systematic environment is robust, scalable, and fit for both research and live trading use.
Responsibilities
The successful candidate will bring deep knowledge of equity datasets, point-in-time data design, vendor methodologies, and data quality curation. They will act as a key link between investment users, technology teams, and central stakeholders to ensure equity data is implemented and maintained to a high standard.
Responsibilities will typically include:
- Own the business logic and curate high-quality downstream datasets for systematic equity research and production use.
- Work with systematic researchers, portfolio managers, developers, and the central Data team to derive data specifications from investment requirements and ensure datasets are fit for purpose for backtesting, signal research, portfolio construction, risk management and production trading.
- Apply deep expertise in equity datasets, point-in-time behaviour, vendor methodologies, corporate action treatments and security master structures to ensure data is usable, historically correct, and well understood.
- Define and enhance data quality controls, validation processes, and monitoring for systematic equity datasets.
- Improve data models, transformation logic, and access patterns in partnership with Technology teams, and contribute to the Systematic Tech codebase.
- Validate vendor-delivered data, and maintain clear documentation of lineage, definitions, caveats, and user guidance.
What makes a great candidate
- Strong technical skills, including Python and SQL.
- Strong understanding of data management, lineage, and data quality principles.
- Ability to translate business requirements into clear data specifications and usable datasets.
- Strong understanding of equity data and historical dataset construction for systematic use cases.
- Ability to identify data caveats, inconsistencies, and implementation risks.
- Excellent problem-solving skills and attention to detail.
- Strong communication skills and ability to explain technical issues to front-office stakeholders.
- Ability to work across research, technology, and data teams.
- Ability to manage multiple priorities under tight deadlines.
- Experience contributing to a shared codebase.
- An Undergraduate Degree in a relevant subject
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We would also prefer you to have
- Experience in a similar role within the financial industry, ideally supporting systematic investing, quantitative research, or equities teams.
- Proven experience curating datasets for systematic research and production use.
- Detailed knowledge of equity datasets, including pricing, security reference, fundamentals, text, and alternative data sources.
- Strong understanding of point-in-time data concepts and best practices in data processing and analysis.
- Familiarity with equity data vendors, vendor methodologies, and dataset caveats.
- Experience with security master and reference data.
- Proven experience using Python or SQL to interrogate vendor data and structured datasets.
Why join us?
- You can have an impact from day one – we empower and trust our people to leverage their skillsets
- Work on a wide variety of projects alongside exceptionally talented people, often closely correlated to world events and trends
- Deliver demonstrable business value working hand-in-hand with the customer
- Learn from industry experts on how financial markets and world economies work
- Ownership of technical products and projects – actively engage with a wide range of business functions to leverage their knowledge and exposure
- Exercising judgement and acumen to understand the true business need beyond the stated requirements
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