Util is an Oxford and London based financial technology company providing investors with actionable data and metrics to make responsible investment decisions. Solving the world's major problems requires an estimated $4trn a year, and such amounts can only be serviced by mainstream investing. To support the asset management community in investing more responsibly, Util has developed a unique methodology, powered by machine learning, to holistically analyze the financial and non-financial value companies create and destroy for all their stakeholders.
Util's methodology is developed alongside world-class academics and practitioners, and over 2018 Util will seek to develop its product offering alongside it's two commercial partners, Hermes and ACTIAM (together managing $130bn assets), to bring its flagship data and analytics to the financial services industry, a $28.7bn global market.
You will be our first data engineering hire, working alongside the co-founders as we seek to build and scale our data acquisition, delivery and storage processes. This is a role that requires significant expertise, creativity and ambition. Expertise to manage the lifecycle of our data projects, creativity to arrive at innovative and scalable solutions to our data challenge and ambition to scale the data engineering team as Util grows in its data and product offering.
We are excited by the technical challenges that our business model and methodology provide the data science and engineering team. Our mission is to try to find automated and accurate ways of identifying non-financial company performance, using the tools of data engineering and data science to provide mainstream investors with a game-changing dataset and methodology to help change the way we invest. You will be working alongside world-class investment experts and advised by top academics, including a Nobel prize winning economist.
Your role will focus specifically on designing and implementing bulk data processing and streaming pipelines as well as data and model storage systems. Your role will be to generate and clean the data needed by the data science/ML team. Additionally, you will be in charge of building scalable APIs, ensuring the data produced and processed by the company is available to our B2B clients. All this will be done while ensuring the system is scalable to huge datasets.
Your role will be critical to the success of Util and will involve constant interaction with Util’s growing data science and commercial capability. The many tasks you will be working on include:
- Making our codebase production ready and suitable for use by investment managers and quant funds;
- Building the B2B API, and ensuring it is low-latency and usable by quant investment funds;
- Designing and building the data pipelines that feed our methodological models. These pipelines will source data from websites, news articles, social media feeds, etc.
- Extensive, evidenced data engineering experience;
- Excellent knowledge of Python and working in a Python-based stack;
- Experience with Hadoop, Spark, Docker, Cloud hosting (ex. AWS), etc;
- Experience with devops and building scalable infrastructure;
- Experience with machine learning, and can understand how to interface code to work with ML models;
- Familiarity with NLP and other ML areas to understand what the data science team is building.
- You enjoy working in a fast-paced environment with high-stakes. You can adapt to new requirements quickly, modify and ship code frequently and address any bugs/errors at quick notice;
- You have a passion for using forefront technology to solve some of the world’s most intractable challenges;
- You are an excellent team-player and enjoy working in a tight-knight group of colleagues;
- You are most comfortable in a position of constant learning and teaching, supporting others and widening your skillset;
- You must be able to work in either London or Oxford, with some flexibility between the two locations;
- You exhibit strong leadership qualities, and are excited about building a top-quality team to support your work with Util.
- Some formal work experience is required. Startup or financial service experience preferred;
- Evidenced formal and informal training relating to the requirements detail in this job description;
- Experience working with financial organisations;
- Experience working in a fast-paced startup environment;
- Experience leading a team to deliver on technical projects;
- Experience building ML systems, particularly NLP;
- Experience building production-ready code, with knowledge of concepts including test-driven development, agile development, etc.
- GBP40-50k per annum
- 0.5 – 1% equity
- 0 – 1.5% performance related equity
- 6m probation
- Negotiable benefits package
- 23rd March
To apply, please email your CV to Stephen@util.co.