Data analyst

Key Responsibilities/Accountabilities:

• Business needs analysis

  Receive requests for data, engage and collaborate with internal and / or external stakeholders to understand business data requirements and proactively interrogate stakeholders to ensure that performance data are delivered in an appropriate format and to the desired specifications.

• Data sourcing

  Identify and evaluate alternate, available, and relevant data sources to ensure reliability, validity, and simple, efficient access to appropriate source data. Locate and remove duplicate sources of data and download and store required data resources in a chronological structure. Where required, work with other analysts and data engineers on quality assurance of source data and systems.

• Data cleaning

  Identify and resolve any ad hoc and / or persistent data quality and integrity issues by conducting both routine and ad-hoc data cleaning and testing, to facilitate the generation of aggregate and up-to-date performance data in a timely manner while also meeting the principles relating to accuracy, integrity, completeness, and adaptability.

• Data processing

  Perform data pre-processing (i.e., data manipulation, transformation, normalization, standardization, visualization, and derivation of new variables/features), as applicable to developing specific algorithms or models. Build rules to transform the data into normalized data and / or report formats, depending on the needs of Model Development. Compile, sort and organizes data in preparation for subsequent analysis.

• Data analysis

  Discover and apply insights from big data sets of structured, semi-structured, and unstructured data to support business performance, client experience, overall execution of the strategy and decision making. Apply data mining techniques, perform statistical analysis on large data sets and validate analysis using appropriate techniques (applying test data sets, A/B testing, scenario modelling, etc.).

• Stakeholder engagement

  Form productive networks with internal and external stakeholders. Collaborate to develop / enhance existing customer behavior predictive models to meet specific business needs. Work with data analysis colleagues across the group to review, approve, produce, or update system or object data models and correlate these with bank models. Work with database design or administration teams to translate object and data models into appropriate database schemas within design constraints.

• Quality assurance

  Ensure all data solutions are delivered within required standards and agreed timelines. Quality assure work completed by junior colleagues, including code and performance reports developed and supporting documents. Review work done by data analysts to assure compliance with standards, methods and tools used in the bank for business information such as Power BI, SQL, etc.

• Reporting

  Lead, develop and generate routine and ad-hoc reports, dashboards, and performance data fact sheets in line with business requirements (i.e., in the required formats and with the relevant visualizations and commentary). Prepare interpretation of finding into clear, actionable, and timely insights and present these to internal and/or external clients.

• Data Strategies, policies, procedures, systems standards, and tools

  Develop and document policies, data strategy, procedures, governance guidelines and SLAs. Comply with all applicable policies, standards, systems, processes, and procedures and technical policies so that all relevant data and governance requirements are fulfilled while consistently delivering quality banking services.

• Data stewardship

  Drive consistent standards for data management and analysis tools and techniques and business data need for structured and unstructured data are consistently met. Ensure that strong controls are in place to deliver data that is fit for purpose within the business.

Additional Information

Competencies:

• Data Analysis

  Competency Description: Ability to analyze statistics and other data, interpret and evaluate results, and create reports and presentations for use by others.

• Data Integrity

  Competency Description: The ability to ensure the accuracy and consistency of data for the duration that the data is stored as well as preventing unintentional alterations or loss of data.

• Metadata management

  Competency Description: The knowledge and understanding of the IT systems and processes that are available to be used for the sharing, storing and retrieval of information in the organisation.

• Statistical and mathematical analysis

  Competency Description: The ability to build, analyse and interpret numerical and non-numerical data to determine potential risk exposure and statistical inferences to inform business decisions.

• Functional Analysis and UAT

  Competency Description: Skills and knowledge of activities, tasks, practices and deliverables to analyse and translate client needs and test the function of the system against the functional requirements.

• Write Code

  Competency Description: Ability to write programming code based on a prepared design.

• Articulating Information

  This competency is about effectively expressing ideas and concerns, giving presentations, explaining things to others as well as showing confidence in the interaction with other people, both strangers and acquaintances alike.

• Challenging Ideas

  This competency is about an individual facilitating or catalyzing change in an organization. Challenging Ideas emphasizes individual behaviors associated with questioning assumptions, challenging established views and arguing personal perspectives.

• Data Analysis

  Ability to analyze data, interpret and evaluate results, and create reports and presentations for use by others.

• AI

  Ability to leverage AI as an analytics transformation tool.

Qualifications

• Minimum requirement is a bachelor’s degree in business / Statistics / business computing / Information Technology / Information Systems / Computer Science or related field.
• Power BI, SQL, Python and R experience.
• 5-7 years Collecting and analyzing critical business data, transforming data and maintaining high levels of integrity in data management. Data sharing, sourcing data from third parties for validation purposes and as well as the service delivery of analyzed critical data to business.
• 5-7 years experience and daily usage of structured query language (SQL), and other common programming languages. Highly advanced computer skills are required for this job. Understands business trends and the direction technology must take to support the business.
• 5-7 years' experience with and understanding of financial and nonfinancial performance data and terminology within Banking. Understands Bank products and services, and business processes.