Data Analyst

Prudential's purpose is to help people get the most out of life. We will deliver our purpose by creating a culture in which diversity is celebrated and inclusion assured, for our colleagues, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and in exchange, we support our people's career ambitions. We pledge to make Prudential a place where you can Connect, Grow and Succeed.

The Data Analyst role is a generalist role that requires base knowledge in the core responsibilities and technical stack used by the Data Analytics Centre of Excellence (CoE). Data Analysts are required to perform various activities that support the growth of the business, collaborate with the business functions and ensure our team continues to get better every day.

Data Analysts are purposely not pigeonholed into one domain (Data Science, BI, Data Engineering) because we aim to get Analysts ready to specialize (if they want to) or develop into as a Senior Analyst. As a result, Data Analysts must be flexible to perform various activities across various technologies.

The role requires an understanding of basic concepts in modern analytics, data engineering, BI and data science. This includes an ability to programmatically work with data, basic statistics, data visualization and some machine learning abilities.

The Data Analyst role is a generalist role that requires base knowledge in the core responsibilities and technical stack used by the Data Analytics Centre of Excellence (CoE). Data Analysts are required to perform various activities that support the growth of the business, collaborate with the business functions and ensure our team continues to get better every day. They work with all divisions across the business.

Enhance the team

The Data Analyst is, of most significance, a team player. As a result, we expect the DA to- Participate in planning, learning and team improvement processes- Share what they have learnt with the team in informal and formal sessions- Help support, train and onboard new staff, trainees, Management Associates (MAs) and graduates- Provide constructive feedback to their management, peers and juniors that helps grow improve the team.- Use your passion for data and technology to identify new technology, methods and ways of working and introduce these to the team.

Demand request pipeline

The Data Analyst will play a vital role in managing and executing on our pipeline of requests.- Primarily, the Analysts ensure the BAU workloads is managed- The BAU tickets are scheduled, completed, documented, and even stopped- BAUs are enhanced so they maintain quality and accuracy while the time to complete is reduced- Requests are analysed and enhanced so they can be executed on newly implemented systems- Analysts are required to review and anlyse legacy processes and enhance them.

Ad Hoc Analytics and Extractions

The Data Analyst will analyze, develop and ensure that ad hoc extractions and analysis are completed according to principles of quality, accuracy, readability and repeatability.- Ad hoc data extraction requests will be completed according to our principles (adds value to the business, documented, code reviewed and managed in source repositories)- Ad hoc data analysis requests will be completed according to our principles (adds value to the business, documented, code reviewed, managed in source repositories and answers the business problem/adds value and is not just doing what the stakeholder wants)- The process of doing ad-hocs is always improved. Data Analysts will improve the business analysis (BA) process, documentation, code management of the team.

Automations (Automated Workflows)

The Data Analyst will support the development of automated workflows that support key business processes aligned to the business strategy.- Set up of all artifacts required for the workflow (Jira, Confluence, BitBucket, Azure and DataBricks)- Work with stakeholders on requirement gathering and business case justification- Design technical solution within our technical stack- Contribute to required documentation- Support stakeholders with the UAT design and write unit tests to ensure quality work- Create technical artifacts to support the deployment process- Manage code in source code repository

Studies and Advanced Analytics

The Data Analyst will support detailed studies into customer behavior and business performance. They will also support the development, design, deployment and monitoring of machine learning models.- Extract data necessary for studies- Undertake Exploratory Data Analysis on datasets- Undertake detailed analysis on datasets- Write-up study design, findings, and recommendations for business stakeholders- Develop features (feature engineering) to support new and existing machine learning models- Support the modelling process (model selection, runs, tracking, analysis and validation)- Develop model monitoring processes

**Skills**:
Tec