DATA ANALYST

This position involves engaging with investors to translate their needs into technical solutions, developing and maintaining data products, ensuring data quality, and collaborating across teams to enhance data strategy, all while prioritising the firm’s core sustainable investment objectives.

THE KNOWLEDGE, EXPERIENCE AND QUALIFICATIONS YOU NEED

As a team we are committed to investing in your future and will be providing support and training to make you a success.

• Whilst this role is within Investment, you will need to have coding abilities (preferably SQL/Snowflake and Python) to enable you to tackle ad-hoc or lightweight solutions
• Experience in data visualisation and analytics tools (i.e. Alteryx, Tableau, Power BI) is desirable
• Data is at the heart of the group. Being comfortable handling large volumes of data and being able to communicate both data and technical issues to a non-technical audience will be fundamental to your day-to-day role
• You will be interacting with investors from all our asset classes; understanding their data challenges, investment process and portfolio construction would be beneficial
• We will be advocates for a continuous improvement culture. An agile mindset with a desire to learn, innovate, educate and collaborate is essential

Sustainability is core to the firm. You will need to have a desire to support this mission and a want to build your knowledge of our critical models and data sets. Your role will involve a diverse array of responsibilities, with the following key tasks at the forefront of your contributions.

• Work with investors to understand and translate their requirements into technical solutions
• Architect, model, build and support data products critical to our investment process using modelling, visualisation and analytics tools
• Collaborate with software developers and data engineers using enterprise supported technology products to deliver robust and supportable solutions
• Addressing investor or user questions on model outputs, data sources or methodologies
• Be involved with the continuous review and development of models and model metrics including impact analysis
• Develop processes and controls to support oversight of data quality monitoring e.g. Detecting anomalies or defects in model output. This includes providing appropriate support for reporting sign offs for model output, and over-rides to erroneous data within our proprietary models
• Work in partnership with teams across the firm to improve our data strategy and its implementation to ensure that we can effectively utilise data assets in the context of our domain