Data Analyst

We are looking for an experienced professional to join our team as a Data Analyst for the Tasman portfolio, a performing Residential Primary dwelling & BTL Tracker portfolio. Reporting to the Senior Customer Contact Operations Manager. In this role you will ultimately be responsible for developing the MI suite to support day to day servicing activities, portfolio monitoring and management and staff performance for the delivery of services to a third-party client, who own the portfolio.

As a Data Analyst at Mars Capital, the individual will be key to our data-driven decision-making process. This role focuses on harnessing, analysing, and interpreting real estate, economic, portfolio and finance datasets to develop refined analytical tools and financial models.

These models and tools will play a pivotal role to analyse and interpret data in a structured templated manner; senior management's strategic decisions; team performance; risk and operations management; portfolio reviews; governance, risk and oversight KPIs; product performance.

The Data Analyst is tasked not only with ensuring data integrity but also with enhancing reporting systems, fostering inter-departmental collaborations, and delivering actionable insights to organisational teams and the leadership team.

Responsibilities:

1. Data Management & Interpretation:

• Harness, analyse, and interpret datasets to aid in data-driven decisions.
• Ensure data integrity across all analysis and reporting, including regular checks for accuracy and consistency.
• Design and implement enhanced reporting systems to streamline the flow of data and optimize data quality.
• Identify trends, patterns, and anomalies in data to provide actionable insights.

1. Analytical Tools & Financial Modelling:

• Establish and continually refine analytical tools, financial models, and processes.
• Develop interactive dashboards that combine visuals with real-time data, including external data sources, to track key performance indicators (KPIs) such as call volume, abandon rate, average queue answer time, average handling time, customer satisfaction, and agent performance. to present insights and analysis for stakeholders.

1. Collaboration & Support:

• Work closely with the contact centre team, providing them with analytical tools and data insights to facilitate their processes.
• Foster inter-departmental collaborations, especially with the IT, development, and contact centre Management teams, to improve data management practices and adhere to best standards.
• Translate technical data into simpler language, delivering recommendations, insights, and conclusions to various stakeholders, from operational teams to senior management.

1. Reporting & Performance Monitoring:

• Generate consistent management information reports that shed light on operational processes, portfolio performance, and system performance.
• Monitor and analyse data model performance, ensuring they align with governance, risk, and oversight KPIs.
• Create ad hoc reports as required by management to support specific initiatives or address urgent issues.
• Undertake specialized research and analysis based on ad hoc business needs, particularly in areas related to product performance.

1. System Optimization & Continuous Learning:

• Create and maintain comprehensive data and system catalogues, detailing data and business definitions, metrics, dimensions, dashboards, and analytical models.
• Design, perform, and analyse A/B tests on all models and dashboards to ensure they meet the evolving needs of the business and the market at large.

Requirements

• Outstanding mathematical, analytical and problem-solving skills;
• Excellent data wrangling skills from discovery to publishing;
• Clear experience in database interrogation, analysis tools and data visualisation, including the use of SQL (Power BI a plus)
• Understand big data and how to clean the data along with ETL processes and building algorithms to manipulate and analyse them efficiently;
• Exceptional communication and presentation skills for explaining your work to people who don't understand the mechanics behind data analysis;
• Effective listening skills for understanding the requirements of the business;
• Excellent planning, time management and organisational skills;
• The ability to deliver under pressure and to tight deadlines with flexibility to adapt in a changing environment;
• Excellent attention to detail;
• Teamworking skills and a collaborative approach to sharing ideas, insights and finding solutions;
• Excellent knowledge of databases (relational & non-relational) and experience working with and creating data architectures;
• Experience of working in a development team in an agile environment;
• Knowledge of AI and machine learning is desirable;
• Familiarity with the banking sector will be advantageous.