Data Analyst

at  Vanguard

Analyzes data, assesses trends and develops actionable insights and recommendations in support of business objectives. Trains and develops junior analysts.

THE OPPORTUNITY

The UK Personal Investor (UKPI) business relies on data and analytics to understand our clients and make business decisions to improve our clients’ chances of investment success. This data and analytics support comes from the CDAO (Chief Data & Analytics Office) division in Europe - part of Vanguard’s IT department. This division was created in 2023 after the launch of global CDAO to centralise data & analytics capabilities and transform how crew use data so that clients and investors can thrive.
Within the CDAO UKPI Data & Analytics team, we’re looking for an experienced, collaborative and self-motivated data analyst, with a passion for data and understanding individual investors. Leveraging a universe of data through a data lake, you will work across multiple UKPI initiatives, delivering data capabilities to analyse data, assess trends and develop actionable insights and recommendations in support of business objectives. Day-to-day activities include building scripts, querying data, designing data visualisations (including dashboards), optimising data infrastructure, identifying automation opportunities, and collaborating with stakeholders across Product, Client Experience, Operations, Marketing, Finance, IT, and Architecture
This role plays a critical role in enabling UKPI’s priorities, and is a great opportunity to embedded in a team that supports UKPI’s long-term strategic vision.
In return we offer an attractive base salary, annual performance bonus paid in January, Partnership bonus paid in June, and competitive benefits. At Vanguard we work Monday to Friday and our staff in most roles work in the office on Tuesdays, Wednesdays and Thursdays, with Mondays and Fridays working from home. As one of the world’s largest asset management firms, Vanguard can offer unrivalled career opportunities in Manchester, the UK, and further afield.

In this role you will:

• Collaborate with our UKPI partners and frame business problems to define analytical frameworks and approaches with a focus on business outcomes, to enable UKPI objectives.
• Collect and prepare structured and unstructured data, and verify its quality, accuracy, and reasonableness.
• Perform data analysis to surface trends and insights using analytical methods and connecting data sources.
• Build advanced scripts in SQL and Python by connecting a series of databases in the UKPI data lake.
• Design and deliver advanced self-serve capabilities, data visualisations (including Tableau and PowerBI dashboards) and internal presentations that translate analytic insights into tangible, actionable solutions for business and IT partners to implement.
• Iterate on existing data assets and provide quick turnarounds to ad-hoc insight requests from stakeholders.
• Deliver and manage the end-to-end lifecycle of data projects, working closely with technical and non-technical across departments and regions.
• Own and optimise recurring analytic or reporting processes, including providing automation solutions.
• Align with and evolve agile work management frameworks (including documentation).
• Invest time in upskilling on technical data tools, concepts and frameworks, and share learnings with the team.
• Train and develop junior analysts.

What we are looking for:

Technical skills:

• Strong experience in a data analyst/science role within the finance industry.
• Bachelor’s and/or Masters in a highly quantitative degree discipline (e.g. Mathematics, Statistics, Finance, Computer Science or Economics) desired.
• Advanced SQL and Python to extract data from multiple sources, perform detailed analysis and automate processes.
• Strong proficiency in building data visualisation dashboards in Tableau (PowerBI is also desirable).
• Experience with AWS (particularly Athena, S2 and glue ETL).
• Comfortable working in an Agile framework and using Agile tools (including JIRA).

• Proven experience presenting complex data finding and concepts to business stakeholders of varying levels of data literacy.

  Mindset & Behaviours:

• Keen interest in analytics and data-driven decision making, demonstrating knowledge of how your role directly impacts the business and telling stories through data.

• Ability to self-manage and self-motivate, with an ability to learn quickly, proactively deliver and communicate results, and take accountability for the team’s goals as if they were your own.
• Ability to communicate effectively (verbal and written) with a range of cross-functional teams, including communicating technical concepts to non-technical audiences.
• Proactivity to shape the team’s work, demonstrate situational adaptability and end-to-end knowledge of a product, collaborating with teams across departments and subdivisons.
• Strong ability to engage with key work partners, encourage others to share diverse ideas, and drive engagement in the team by sharing expertise and being recognised as a trusted adviser.

• Collaborate with our UKPI partners and frame business problems to define analytical frameworks and approaches with a focus on business outcomes, to enable UKPI objectives.
• Collect and prepare structured and unstructured data, and verify its quality, accuracy, and reasonableness.
• Perform data analysis to surface trends and insights using analytical methods and connecting data sources.
• Build advanced scripts in SQL and Python by connecting a series of databases in the UKPI data lake.
• Design and deliver advanced self-serve capabilities, data visualisations (including Tableau and PowerBI dashboards) and internal presentations that translate analytic insights into tangible, actionable solutions for business and IT partners to implement.
• Iterate on existing data assets and provide quick turnarounds to ad-hoc insight requests from stakeholders.
• Deliver and manage the end-to-end lifecycle of data projects, working closely with technical and non-technical across departments and regions.
• Own and optimise recurring analytic or reporting processes, including providing automation solutions.
• Align with and evolve agile work management frameworks (including documentation).
• Invest time in upskilling on technical data tools, concepts and frameworks, and share learnings with the team.
• Train and develop junior analysts